Citadel Wraith is the AI-powered digital forensics and incident investigation platform that reconstructs breaches from millions of data points, preserves evidence with court-admissible chain of custody, attributes attacks to adversaries, and transforms every incident into intelligence that prevents the next one. The attacker deleted their tracks. Wraith recovers them.
When the breach is over, the real work begins. What happened? When did it start? How did they get in? What did they access? What did they take? Are they still here? Will it hold up in court? These questions cannot be answered with guesswork. They require forensic precision — bit-for-bit disk images, volatile memory captures, network traffic reconstruction, malware reverse engineering, and timeline correlation across millions of events. A single incident now generates data from dozens of systems across cloud, on-premises, and endpoint environments. Traditional manual DFIR methods cannot keep pace with the volume, the complexity, or the urgency.
Wraith transforms DFIR from an artisanal craft performed by a handful of elite specialists into a scalable, AI-augmented investigation platform. It does not replace human investigators — it amplifies them. AI clusters 1,500 log entries into behavioral groups in seconds. ML classifies malware samples against known families automatically. LLMs generate investigation summaries that transform raw data into coherent attack narratives. And throughout, every action, every artifact, every conclusion is documented with a tamper-evident chain of custody that satisfies the most demanding court, regulator, or insurer.
Wraith provides end-to-end digital forensics — collection, preservation, analysis, reconstruction, attribution, and reporting.
Traditional forensic evidence collection is manual, slow, and error-prone — and every minute of delay risks volatile evidence being overwritten. Wraith automates collection at scale: remotely acquiring disk images, memory dumps, event logs, registry hives, browser artifacts, cloud audit trails, and network captures from thousands of endpoints simultaneously. Every artifact is hashed (SHA-256) at collection, timestamped, and logged into a tamper-evident evidence ledger. The system prioritizes volatile evidence — running processes, network connections, memory-resident malware — that will be lost when systems are powered down.
The most sophisticated attacks never touch disk — they operate entirely in memory, invisible to traditional forensics. Wraith's memory forensics engine captures and analyzes volatile memory from compromised systems, using ML models to identify hidden processes, code injection (DLL injection, process hollowing, reflective loading), rootkit hooks, encryption keys, credential material, and command-and-control communication artifacts. The engine reconstructs the in-memory state of the system at the time of compromise — revealing what the attacker was doing even when they left no files behind.
Understanding the malware used in an attack reveals the adversary's capabilities, intent, and identity. Wraith's malware analysis engine performs automated static analysis (code structure, API imports, strings, packing detection) and dynamic analysis (sandbox detonation with behavioral monitoring) simultaneously. ML models classify samples against 10,000+ known malware families, identify variants of known threats, and flag previously unseen malware based on behavioral similarity. The engine extracts C2 infrastructure (IP addresses, domains, communication protocols), persistence mechanisms, and lateral movement capabilities — providing the intelligence needed for complete eradication and accurate attribution.
Network forensics reveals the attacker's movement across the environment — what they accessed, what they exfiltrated, and where they communicated. Wraith analyzes full packet captures, NetFlow data, DNS query logs, proxy logs, and firewall records to reconstruct the network activity timeline. The engine identifies C2 beaconing patterns in encrypted traffic (using JA3/JA3S fingerprinting and behavioral analysis), detects data staging and exfiltration volumes, and maps lateral movement pathways across the network. Every network connection associated with the attacker is identified, timestamped, and correlated with endpoint and identity evidence.
Cloud environments shatter traditional forensic assumptions — there are no disks to image, no physical servers to seize, and ephemeral containers may have been destroyed before the investigation begins. Wraith's cloud forensics engine collects and analyzes cloud-native evidence: CloudTrail/Activity Logs/Audit Logs, IAM policy changes, S3/Blob/GCS access logs, VPC flow logs, container image layers, Kubernetes audit logs, and serverless function invocations. The engine reconstructs attacker activity across cloud services, identifies compromised IAM credentials, and traces data access and exfiltration through cloud-native pathways.
The ultimate product of a forensic investigation is not data — it is a story. What happened, in what order, through what mechanism, with what impact. Wraith's timeline engine correlates events across all evidence sources — endpoint logs, memory artifacts, network captures, cloud audit trails, identity events, and malware behavior — into a single, chronologically ordered attack timeline. LLMs then transform this timeline into a coherent narrative: describing each phase of the attack in clear language, mapping activities to MITRE ATT&CK techniques, and producing investigation reports readable by executives, regulators, insurers, and prosecutors.
Forensic evidence is worthless if it cannot survive legal scrutiny. Wraith maintains a cryptographically secured chain of custody for every artifact: who collected it, when, from which system, using which method, and every subsequent access, analysis, and transfer. Evidence hashes are verified continuously, and any integrity violation triggers an immediate alert. The system generates regulatory notification packages (GDPR 72-hour, SEC 4-day, state breach notification), insurance claim documentation, law enforcement evidence packages, and litigation-ready exhibit binders — all from the same evidence repository with consistent, verified integrity.
The most valuable outcome of a forensic investigation is not the report — it is the intelligence that prevents the next incident. Wraith automatically extracts IOCs (file hashes, IP addresses, domains, registry keys, behavioral patterns) from every investigation and pushes them to your threat intelligence platform and SIEM detection rules. The system identifies which existing detection rules failed (and why), generates updated rules, and recommends SOAR playbook modifications based on observed attacker behavior. Lessons-learned documentation is auto-generated with specific, actionable recommendations — not generic advice, but "here is the exact detection rule that would have caught this attack 14 days earlier."
The AI triage changed how I investigate. I used to spend the first two days of every investigation manually reviewing logs — tens of thousands of entries, searching for the needle. Wraith clustered 4.2 million log events into 340 behavioral groups in 90 seconds. I went from reading every log entry to reviewing 340 summaries, each one pre-classified by the AI with MITRE ATT&CK mapping and confidence scoring. I found the initial access vector in the fourth cluster I reviewed. That moment — when I realized this tool had just saved me 48 hours of manual work on day one — I knew forensics had changed forever.
The memory forensics capability caught what everything else missed. The insider was using an encrypted in-memory tunnel — no disk artifacts, no DNS queries, no browser history, nothing in DLP. Our EDR saw nothing. Our SIEM saw nothing. Our DLP saw nothing. Wraith saw it in volatile memory. It recovered the encryption keys and decrypted the tunnel traffic. Fourteen thousand client records. Three months of exfiltration. Without memory forensics, we would still believe the data was safe. The evidence held up in criminal court. The insider was convicted.
Our cyber insurer required a complete forensic investigation before they would process our $18 million claim. They told us to expect 3-4 weeks. Wraith completed it in 6 hours. Not a preliminary assessment — the full investigation. Root cause identified. Scope determined. Data exposure quantified. Timeline reconstructed with MITRE ATT&CK mapping. Chain of custody documented. Regulatory notification package generated. Our insurer's forensic reviewer called it "the most thorough and well-documented investigation report I have reviewed in twelve years." The claim was approved in full.
Engage the Citadel Wraith team for incident investigation, forensic readiness assessment, or DFIR retainer services.