{"data":{"id":"8d81a063-9d2c-44a3-8274-99b81ca01953","title":"LLM Development Risks: Security Threats and Mitigation Strategies | Endor Labs","summary":"Endor Labs published a guide on LLM development risks, covering insecure generated code, hallucinated dependencies, leaked secrets, and supply chain issues. It explains that LLMs blur the line between data and instructions and produce non-deterministic outputs, which existing security tools were not designed to catch. The guide draws on the OWASP Top 10 for LLM Applications and cites a JAMA Network Open study reporting a 94.4% success rate for direct prompt injection in controlled medical LLM dialogues.","solution":"N/A -- no mitigation discussed in source.","labels":["security","industry"],"sourceUrl":"https://www.endorlabs.com/learn/llm-development-risks-security-threats-and-mitigation-strategies","publishedAt":"2026-10-12T15:59:35.000Z","cveId":null,"cweIds":null,"cvssScore":null,"cvssSeverity":null,"severity":"info","attackType":["prompt_injection","data_extraction"],"issueType":"news","affectedPackages":null,"affectedPackageNames":null,"affectedPackageRefs":null,"affectedVendors":[],"affectedVendorsRaw":[],"classifierModel":"claude-haiku-5-5","classifierPromptVersion":"v4","summaryPromptVersion":"v2","headline":null,"headlinePromptVersion":null,"cvssVector":null,"attackVector":null,"attackComplexity":null,"privilegesRequired":null,"userInteraction":null,"exploitMaturity":null,"epssScore":null,"epssCheckedAt":null,"kevDateAdded":null,"advisoryAliases":null,"affectedPackagesSource":null,"affectedPackagesCheckedAt":null,"patchAvailable":null,"disclosureDate":"2026-10-12T15:59:35.000Z","capecIds":null,"crossRefCount":0,"attackSophistication":"moderate","impactType":["confidentiality","integrity"],"aiComponentTargeted":null,"llmSpecific":true,"classifierConfidence":0.85,"researchCategory":null,"atlasIds":["AML.T0051"]}}