Attack Type
Model Poisoning
Model poisoning involves corrupting machine learning models during training by injecting malicious data, modifying model weights, or tampering with the training pipeline to create backdoors or degrade performance.
30
Total CVEs
2
Pages
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Current
| Severity | CVE | Headline | Package | CVSS |
|---|---|---|---|---|
| HIGH | CVE-2025-7707 | llama-index: world-writable NLTK dir allows local tampering | llama-index | 7.1 |
| HIGH | CVE-2025-7647 | llama-index-core: insecure /tmp dir, model theft risk | llama-index-core | 7.3 |
| MEDIUM | GHSA-j343-8v2j-ff7w | picklescan: scanner bypass allows pickle-based RCE | picklescan | - |
| MEDIUM | GHSA-r54c-2xmf-2cf3 | ms-swift: RCE via pickle deserialization in adapter models | - | |
| MEDIUM | CVE-2025-3044 | llama-index ArxivReader: MD5 collision corrupts training data | llama-index-readers-papers | 5.3 |
| MEDIUM | CVE-2025-0508 | SageMaker SDK: MD5 collision silently replaces ML workflows | sagemaker | 5.9 |
| MEDIUM | CVE-2024-7041 | open-webui: IDOR enables cross-user memory tampering | open-webui | 6.5 |
| HIGH | CVE-2026-28788 | Open WebUI: BOLA enables RAG poisoning via file overwrite | open-webui | 7.1 |
| MEDIUM | CVE-2026-34450 | anthropic-sdk: insecure file perms expose agent memory | anthropic | - |
| MEDIUM | CVE-2026-35492 | kedro-datasets: path traversal enables arbitrary file write | kedro-datasets | 6.5 |
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AI Threat Alert