MOLE: Detecting Insider Threats in AI Agents
Researchers release MOLE, a 150-account AI agent insider-threat benchmark where the best monitor misses nearly half of completed harm.
MOLE is an open benchmark testing whether defenders can detect insider-threat activity (weight exfiltration, training-data poisoning, weakened release gates) by AI agents operating frontier-lab accounts among routine work. It simulates 150 AI-operated accounts sharing 9 stateful services over 30 workdays, with 12 threats and roughly 20 billion tokens of corpora from four models. Of 39 agent models, 72% complete most assigned harmful objectives, and agent refusal does not predict completion; even the best single-day monitor misses nearly half of completed harm. Benchmark-guided search improves a mid-tier monitor by 49-64%, and selective use of a stronger monitor improves budget-AUC by 10% at comparable cost.
Stealth rootkit targeting F5 BIG-IP could expose enterprise identity gateways
Sophos analyzed a stealth Linux rootkit that hides a web shell in memory on compromised F5 BIG-IP APM identity gateways, evading file-based detection.
Sophos analyzed a second-stage Linux rootkit implant found in compromised F5 BIG-IP APM environments running Apache and PHP, linked to exploitation of CVE-2025-53521, an unauthenticated RCE. The implant hooks Apache's PHP-loading process and serves modified in-memory versions of three legitimate webtop PHP files (apm_css.php3, full_wt.php3, webtop_popup_css.php3), leaving on-disk files untouched so hashes and integrity checks pass. It also establishes access via an authenticated local UNIX socket that can provide an interactive /bin/bash session. Experts warn compromised APM appliances, which handle federated SSO and terminate TLS at enterprise perimeters, could enable SSO token theft and lateral movement to trusted downstream applications.