PlatformAI-generated from public sourcesThe starting point for every profile: auto-generated by 0-Doubt from public vendor materials, and not yet confirmed by the vendor or an independent analyst. Nothing here is hidden or overstated — it simply has not been reviewed yet.Where every profile starts, before the vendor or an analyst has reviewed it. A higher label means a more independent source — not a better product.How trust works →Secure coding rating: 30/100How this score is computedA product with no known CVEs starts at a neutral score and climbs the longer it goes without one; a product with known CVEs is penalized by severity instead. This one has 2 known CVEs (vendor-level match — see the CVE list below) and is tracked as ~115 days old in our catalog (a stand-in for real release date, which we don't track). The platform admin controls the formula's weights.
Unifies threat intelligence, security data, and agentic AI.
Known CVEs (2)About this listSourced from the public NVD database, matched by vendor name. Shown here at the vendor level — we don't track per-product/version data, so a listed CVE may affect a different product from this vendor, not necessarily this one. “New” means published within the last 30 days. “Actively exploited” means CISA's Known Exploited Vulnerabilities (KEV) catalog confirms real-world exploitation, not just a theoretical severity score. An “EPSS” chip appears at 10% and above: that is FIRST's estimated chance of exploitation in the next 30 days, which measures likelihood rather than impact and so can differ sharply from the severity beside it.
Anomali Match before 4.6.2 allows OS Command Injection. An authenticated admin user can inject and execute operating system commands. This arises from improper handling of untrusted input, enabling an…
Anomali Agave (formerly Drupot) through 1.0.0 fails to avoid fingerprinting by including predictable data and minimal variation in size within HTML templates, giving attackers the ability to detect an…
What it does
Anomali's Agentic SOC Platform unifies threat intelligence, security data, and agentic AI to enable security teams to make governed decisions and take action at machine speed. It provides an Intelligent Unification Layer that normalizes and enriches telemetry, a Decision Intelligence Graph that correlates alerts with contextual intelligence, and a Governed Action Engine that investigates and responds under policy with auditability, used by enterprise security teams and public‑sector organizations to turn fragmented data into prioritized investigations.
Strengths
Unifies threat intelligence and security data into one governed foundation.
Provides Intelligent Unification Layer that normalizes, deduplicates, and enriches telemetry.
Decision Intelligence Graph correlates alerts with contextual intelligence and operational memory.
Governed Action Engine investigates and responds under policy with audit‑able, reversible actions.
Autonomy Model progresses workflows from recommendation to approval to act stepwise.
Reclaims 60–70% of analyst time from false positive triage.
Materials
0
No datasheets, whitepapers, case studies, videos, or demos linked yet.
