AI Security Threat Analysis: A Researcher's Playbook

Evidano transforms fragmented incident data into organized evidence packs. Problem: IR collects fragmented data (chat logs, PDFs, ticket threads, audio notes) that are hard to synthesize. Evidano ingests transcripts, PDFs, emails, and connector logs, and generates time-stamped thematic and quote-level extracts so analysts can reconstruct the chain of influence (who said what, when, and which document triggered behavior).

Evidano helps analysts follow the causal text that influenced model behavior. Problem: Panelists stress the need to reconstruct what the model saw (retrieval traces, prompt framing). Evidano automatically tags retrieved-doc excerpts, builds co-occurrence networks, and applies hierarchical codes so analysts can follow a narrative across sources and surface the exact text that likely influenced an agent.

Evidano enables reproducible comparisons across groups and versions. Problem: You need to know whether a failure was systemic or specific to a segment (team, environment, model version). Evidano runs cross-segment frequency analysis and comparative thematic reports to test whether an event happened more with connector A versus B and to quantify drift over time.

Evidano accelerates red-team iterations and forensic turnarounds. Problem: Manual coding slows red-team iterations and delays fixes. Evidano imports codebooks, applies AI-assisted coding, surfaces representative quotes, and produces ready-to-share visualizations (word clouds, co-occurrence graphs) to shorten the time from finding to mitigation.

Evidano enforces strict handling for sensitive incident material. Problem: Sensitive incident material requires strict handling. Evidano provides enterprise encryption, PII redaction, and a no-third-party-training guarantee to keep analyses private while enabling team collaboration.