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First reported medium.com
Security as Code: AI Agent Security — Poisoned Weights and the Supply Chain You Can’t Scan (Part 3 of 3) | by Vitaliy Zhhuta | Jul, 2026
Part 3 of a 'Security as Code' series by Vitaliy Zhhuta examines AI model supply-chain risk, using an illustrative scenario in which a deleted Hugging Face namespace is re-registered by an attacker and a poisoned 'v2.1' model with clean safetensors format passes CI while carrying a behavioral backdoor. The piece argues that statistical backdoors — weights trained to silently alter behavior on trigger phrases — cannot be detected by malware scanners and have no CVE. Details →First reported firetail.ai
LLM08: Vector & Embedding Weaknesses - FireTail blog posts
FireTail's blog explains OWASP LLM08: Vector and Embedding Weaknesses, covering risks such as unauthorized access, cross-context information leaks, embedding inversion attacks, data poisoning, and behavior alteration in RAG systems that use vector databases. The post lists mitigation techniques including access control, data validation, source authentication, and monitoring. Details →First reported dailyjus.com
Prompt Injection: Are Invisible Instructions the Next AI Risk in Disputes? – Daily Jus by Jus Mundi
Legal analysts at Greenberg Traurig examine prompt injection as an emerging AI risk in legal disputes, describing how hidden instructions embedded in documents can manipulate AI tools that ingest them into producing skewed or incomplete outputs. The piece contrasts this with AI hallucinations and notes a court has already dealt with the issue. Details →First reported aicerts.ai
Undetectable AI Model Backdoors Imperil Neural Security
AI CERTs News synthesizes cryptography research on undetectable AI model backdoors, citing Goldwasser et al. (FOCS 2022) on computationally undetectable injections, NeurIPS 2024 work on obfuscated releases, and Sparse Backdoor constructions reducible to Sparse PCA. It argues that outsourced training, checkpoint marketplaces, and prebuilt adapters let attackers embed triggers that survive static scans, and cites benchmark claims of near-100% trigger activation in tool-using language models. Details →How the wire is made
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