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MemSentry: A Framework for Detecting Persistent Memory Poisoning in Agentic AI
MemSentry intercepts persistent-memory writes in agentic AI to catch memory poisoning, reaching 91.7% accuracy with SBERT+LR classification.
Memory poisoning lets adversaries plant crafted content in an agent's long-term memory to suppress security alerts, enable privilege escalation, or override policies without modifying model weights or system prompts. The paper presents MemSentry, a configuration-driven framework that evaluates proposed persistent-memory writes on source trust, semantic risk, attack radius over a dependency DAG, access risk, and a signed security-state delta to issue deterministic Accept, Review, or Quarantine decisions. Across 1,000 GPT-4-generated scenarios on a 20-asset dependency DAG, SBERT+LR achieved 91.7% accuracy and 0.908 macro-F1, all four classifiers detected 100% of external quarantine-class threats, and verified-insider writes are escalated for human review rather than auto-quarantined.
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BGP Hijack Delivers Malicious Virtualizor Update That Establishes Persistent Root Access
Attackers used a BGP hijack to divert Softaculous traffic and push a malicious Virtualizor update granting root persistence on some hypervisors.
Virtualizor reported that a BGP hijack between August 28 20:57 UTC and August 30 06:10 UTC diverted Softaculous update traffic to an attacker-operated server holding a valid Let's Encrypt certificate. Installations checking for updates during the window could receive a malicious package that added an attacker SSH key to root, created a proxyuser account, and installed a Java payload persisted via a systemd service. Hosting provider AlbaHost confirmed 5 of its 34 Virtualizor hypervisors were root-compromised. Virtualizor shipped Patch 9 with a Security Analyzer on September 1, but cryptographic package signing remains future work.
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