Search the Proof Behind Every Security Story
The Aegisify Digital Intelligence Evidence Ledger is the forensic layer beneath investigations, baselines, and security conclusions. It gives analysts a bounded workspace for searching immutable application evidence, inspecting event-level proof, pivoting across related application context, comparing time windows, and exporting sanitized chain-of-custody packages without treating later interpretation as if it were the original fact.
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Events Are Facts. Investigations Are Interpretations Over Those Facts.
Digital Intelligence is designed so later analytics can evolve without rewriting the event that was originally observed.
What Aegisify observed
Event identity, timing, evidence producer, actor or request context, application object, destination metadata, byte counts where available, privacy-bounded database evidence, integrity fields, and other recorded application evidence remain the proof layer.
What Aegisify concludes later
Baseline state, novelty, attack-stage classification, severity, confidence, incident context, AI explanation, and analyst decisions can add meaning over time without changing the underlying immutable event.
Search Application Evidence by the Context Investigators Actually Use
The Evidence Ledger supports bounded forensic search so analysts can narrow a large event stream without requesting an unlimited data set.
Inspect the Fields That Make the Security Evidence Useful
The exact fields depend on the sensor and event type, but the workbench is designed to expose both the observed fact and the later correlated context around it.
Move From One Event to the Related Application Story
A single event becomes much more useful when the analyst can follow the identifiers attached to it.
Export a Bounded, Sanitized Evidence Package for the Current Search
Digital Intelligence can create a chain-of-custody search package scoped to the current domain, filters, and UTC window.
The current forensic workflow intentionally bounds the export rather than treating the evidence store as an unrestricted dump. The application excludes raw request and response bodies, cookies, authorization headers, secrets, and unbounded payloads from this search-package export path.
This makes the package useful for investigation handoff, evidence review, and auditability while respecting the product’s data-minimization boundary. A bounded export is not the same thing as a legal conclusion; organizations should apply their own evidence-handling and legal requirements to any formal proceeding.
Preserve Security Value Without Copying Everything
Some evidence categories—especially database and source-sensor context—are intentionally represented through fingerprints, semantic fields, bounded metadata, or normalized proof rather than raw sensitive values.
For example, database evidence can describe statement type, query-shape fingerprint, table or schema fingerprints, transaction context, and detected primitives without claiming that raw SQL, raw rows, or credentials were transmitted.
Find Material Change Without Treating More Activity as Automatically Worse
The Evidence Ledger can compare the selected forensic window with the immediately preceding equal-duration period using the same filters.
Analysts can review changes in high or critical evidence, unique actors, routes, resources, external destinations, and observed egress bytes. The comparison is intentionally neutral: more activity is not automatically more dangerous, and less activity is not automatically safer. It is a way to locate meaningful change and then open the underlying evidence.
Use the Ledger as the Proof Layer for the Rest of Digital Intelligence
Evidence becomes operationally valuable when the rest of the product can return to it.
Open Investigations to see how related evidence becomes an attack story and persistence review. Use Data Exposure & Movement to follow destination and protected-data context. Compare Behavior & Trust to understand whether a behavior is first-seen, rare, expected, or affected by an exact-scope analyst decision.
Common Questions About Immutable Application Evidence
What does “immutable evidence” mean in Digital Intelligence?
It means the observed event remains the proof layer while later correlation, baseline state, severity, incident context, AI explanation, and analyst decisions are treated as later interpretation. Those interpretations can evolve without rewriting the original event.
Can I search evidence by request or execution?
Yes. The current forensic workbench supports filters and pivots such as request ID, execution ID, actor or identity, component or resource, destination, severity, producer, event type, outcome, attack stage, and UTC time range.
Does the Evidence Ledger store raw request bodies and secrets?
The current chain-of-custody search export explicitly excludes raw request and response bodies, cookies, authorization headers, secrets, and unbounded payloads. Individual sensors also use privacy-bounded metadata and fingerprints for sensitive evidence categories.
Does a high-severity event prove compromise?
No. Severity helps prioritize observed facts inside their investigation and entity context. A high or critical event should be reviewed with the surrounding evidence; severity by itself is not a complete compromise verdict.
Why keep the Evidence Ledger separate from Investigations?
Because the ledger is the technical proof layer and can become large. Keeping it separate allows analysts to search and inspect detailed event evidence without making the executive investigation narrative compete with the full forensic data set.
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