Finding the Needle — Even When You Don’t Know What It Looks Like

The Moment Every Security Team Dreads

Your team has successfully contained a security incident. The environment is secured. The forensic evidence is preserved. But now you’re staring at a folder containing over 100 gigabytes of deeply nested JSON log files — and you have no clear idea of exactly what the attacker did, or where to begin.

This was the precise situation faced by a financial services client who engaged CyberSolace following a suspected breach. Their security operations team had done everything right in the immediate response phase. The challenge was now understanding the incident in enough detail to satisfy regulatory requirements, notify the right stakeholders, and confidently close every remediation gap.

Why Traditional Investigation Methods Fail at Scale

The client faced three compounding challenges that rendered conventional incident investigation approaches unworkable:

A Different Kind of Investigation

CyberSolace deployed a proprietary analytical toolset powered by advanced AI — operating within the industry-standard MITRE ATT&CK framework — to conduct a forensic investigation unlike anything the client had encountered before.

Rather than relying on rigid, pre-configured search parameters, our AI agents interrogated the log data the way an expert human analyst would — only faster, without fatigue, and without losing context across a 100 GB dataset.

• Contextual Schema MappingThe system automatically ingested the complex log dataset, understood the underlying schema, and mapped relationships across disparate log sources — without manual configuration or pre-knowledge of the environment.
• Heuristic Threat HuntingInstructed to find anomalous behaviours and logical inconsistencies rather than specific known indicators, the AI formed hypotheses, tested them against the data, and followed digital breadcrumbs iteratively — just as a skilled analyst would, but at machine speed.
• Structured & Unstructured Data FusionOur tools bridged the gap between structured log fields and unstructured payload data, correlating events that traditional SIEM platforms would treat as isolated, unrelated anomalies.
• Expert Analyst ValidationAll AI-generated findings were reviewed, validated, and contextualised by our experienced security consultants — ensuring accuracy, professional narrative, and genuinely actionable output.

What We Found

The results of the investigation were transformative. Within the vast dataset, the AI successfully identified lateral movement — attacker activity perfectly camouflaged within what appeared to be legitimate administrative traffic. This was precisely the kind of behaviour that conventional queries would never have surfaced, because no one knew to search for it.

• Illuminated the blind spots. The AI found movements the client didn’t know existed — hidden within normal-looking administrative sessions across the environment.
• Delivered granular visibility. The client received a definitive, second-by-second timeline of the threat actor’s activities, each entry linked to specific log records for auditability and regulatory reporting.
• Enabled targeted remediation. Armed with precise intelligence, the client moved from broad-stroke containment to highly targeted recovery — confidently confirming which systems were accessed, what data was involved, and exactly how the adversary operated.

The investigation satisfied regulatory reporting requirements, gave leadership the clear narrative they needed, and allowed the security team to close the incident with genuine confidence rather than residual uncertainty.

Key Business Benefits

This engagement proved that the traditional model — human analysts manually sifting logs or writing exact queries — is no longer sufficient for modern, complex attacks at scale. Our AI-Powered Security Incident Analysis Service delivers four core benefits: