Where AI Systems Leak Data: A Lifecycle Review of Real Exposure Paths
Praetorian research maps real data exposure paths throughout AI system lifecycles, from training data leakage to operational logging vulnerabilities.
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Praetorian research maps real data exposure paths throughout AI system lifecycles, from training data leakage to operational logging vulnerabilities.
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Security researcher hxr1 introduces MLArc, a C2 framework weaponizing Apple CoreML and Vision AI frameworks for covert offensive operations on macOS.
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Checkmarx discovers HITL Dialog Forging attack that weaponizes human-in-the-loop AI safeguards by manipulating approval dialogs for malicious actions.
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GreyNoise detects surge in threat actors targeting LLM infrastructure, probing for vulnerabilities in model endpoints and AI deployment frameworks.
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Unit42 discloses RCE vulnerabilities in NVIDIA NeMo, Salesforce, and FlexTok AI libraries through unsafe model configuration deserialization.
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Flatt Security research reveals eight attack vectors against Claude Code CLI, demonstrating prompt injection and command execution vulnerabilities.
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Lares Labs analysis reveals OWASP Agentic AI Top 10 threats are actively exploited in the wild, from goal hijacking to cascading multi-agent failures.
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Niyikiza research explores AI agent tool trust boundary gaps where tool descriptions diverge from actual capabilities, creating exploitable security vulnerabilities.
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PromptArmor researchers demonstrate IBM AI coding agent Bob can be manipulated to download and execute malware through prompt injection vulnerabilities.
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Check Point exposes GoBruteforcer malware using AI-generated credential lists to compromise servers for cryptocurrency mining operations.
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