Memory Forensics

Overview#

A threat-hunting analyst investigating a suspected fileless malware infection has no disk artefacts to work from: the attacker loaded a malicious reflective DLL directly into a process, left nothing on the file system, and the endpoint has since been powered down. The analyst acquires a memory image captured just before shutdown, loads it into the Memory Forensics module, and within minutes has a list of injected code regions, decrypted strings extracted from the process heap, reconstructed network sockets, and a process-tree view that shows exactly how the malicious loader was spawned. The evidence, including cryptographic integrity proofs tied to the capture moment, is packaged into the investigation case without leaving the platform.

Memory Forensics provides deep, post-mortem and live analysis of RAM captures using Volatility 3, the leading open-source memory forensics framework. Analysts can enumerate processes, modules, kernel structures, network connections, injected code, and decrypted in-memory artefacts from Windows, Linux, and macOS memory images. Every finding is linked to the originating investigation case, stamped with a classification level, and preserved with a complete chain-of-custody record, satisfying both forensic-evidence integrity requirements and multi-national operational security policies.

Key Features#

• Volatility 3 Integration: The module runs Volatility 3 plugins natively against acquired memory images, providing access to the full plugin ecosystem for Windows, Linux, and macOS targets without requiring analysts to manage a separate toolchain.
• Process and Module Enumeration: Reconstruct the complete process tree, loaded DLLs, and kernel modules present at capture time, including hidden or unlinked entries that evasive malware attempts to conceal from standard OS APIs.
• Injected Code Detection: Identify memory regions flagged as executable but not backed by any on-disk module, a primary indicator of reflective DLL injection, shellcode staging, and process-hollowing techniques used in fileless attacks.
• Network State Reconstruction: Recover active and recently closed network sockets, connection endpoints, and listening ports from memory structures, providing network context even when no packet captures are available.
• Kernel and Rootkit Analysis: Examine kernel pool allocations, driver objects, and SSDT hooks to detect rootkits, bootkits, and malicious kernel-mode components that operate below the visibility of user-space monitoring tools.
• String and Heap Extraction: Extract human-readable strings, decrypted configuration blocks, and heap-resident artefacts from targeted processes, surfacing command-and-control URLs, encryption keys, and operator infrastructure that never appear on disk.
• Classification-Level Enforcement: Each analysis session and its findings carry a secrecy level. Results are filtered against the requesting analyst's clearance, ensuring sensitive memory artefacts from restricted investigations remain visible only to appropriately cleared personnel.
• Chain-of-Custody Preservation: Every memory image ingestion and analysis result is recorded with a cryptographic digest, a trusted timestamp, and an audit trail entry, producing a forensically sound evidence chain from acquisition through disclosure.

Use Cases#

• Fileless Malware Investigation: Recover indicators, payloads, and adversary infrastructure from memory when no on-disk artefacts exist, covering reflective injection, living-off-the-land binaries, and in-memory-only implants.
• Incident Response Triage: Rapidly assess the state of a compromised host by reconstructing the process tree, open network connections, and loaded drivers from a memory snapshot taken during or immediately after an intrusion.
• Rootkit and Kernel Implant Detection: Identify malicious kernel-mode components, hooked system calls, and hidden driver objects that bypass file-system and user-space visibility, including threats that persist across reboots via firmware or boot-sector manipulation.
• Credential and Secret Recovery: Locate in-memory credential stores, decrypted keying material, and authentication tokens retained in process address spaces, supporting both attacker-capability assessment and credential-rotation decisions.
• Threat-Hunt Validation: Confirm or exclude hypotheses about adversary presence by running targeted Volatility 3 plugins against memory captures from candidate hosts, providing an authoritative answer where behavioural telemetry alone is ambiguous.
• Evidence Packaging for Legal Proceedings: Produce integrity-verified, timestamped memory analysis findings with a documented chain of custody suitable for submission to prosecuting authorities or regulatory bodies.

Integration#

Memory Forensics connects to the platform's evidence management, case management, and digital forensics workbench capabilities, so findings from a Volatility 3 analysis session flow directly into investigation cases alongside artefacts from disk forensics, endpoint hunts, and network captures. Memory images can be supplied from live endpoint collection workflows or uploaded as existing capture files. Results feed the shared threat-intelligence layer, where process injection indicators and recovered command-and-control infrastructure are correlated against STIX 2.1 indicators and mapped to MITRE ATT&CK techniques. Classification-level controls and organisation-scoped access apply consistently across all integrated workflows, maintaining multi-tenant isolation throughout.

Open Standards#

• Volatility 3 (open-source): The analysis engine is built on Volatility 3, the community-maintained Python framework for memory forensics; all plugin output is consumed and structured natively by the module.
• FIPS 180-4 (SHA-256): Memory images are verified with a SHA-256 cryptographic digest at ingest and at each custody-transfer event, confirming bit-for-bit integrity of the evidence throughout its lifecycle.
• RFC 3161 (Internet X.509 PKI Time-Stamp Protocol): Analysis findings and evidence exports are bound to trusted timestamps from a configured timestamp authority, establishing a legally defensible proof of existence at a specific point in time.
• W3C Verifiable Credentials Data Model v2.0: Chain-of-custody records for memory images and analysis sessions are issued as signed Verifiable Credentials with DID-based issuers, enabling cross-platform provenance verification.
• ISO/IEC 27037:2012 (Digital Evidence Identification and Collection): Acquisition, handling, and custody procedures follow ISO/IEC 27037 guidance for identifying, collecting, and preserving digital evidence in a forensically sound manner.
• OASIS STIX 2.1: Indicators recovered from memory analysis, including injected module hashes, command-and-control addresses, and mutex names, are expressed and shared as STIX 2.1 indicator objects within the platform's threat-intelligence pipeline.
• MITRE ATT&CK: Memory-resident techniques and injected artefacts identified by Volatility 3 plugins are mapped to MITRE ATT&CK technique identifiers, giving analysts a standardised vocabulary for findings included in incident reports.
• ISO 19005 (PDF/A): Evidence packages containing memory analysis findings can be exported in PDF/A archival variants, satisfying long-term preservation requirements used by prosecuting and regulatory authorities.

Availability#

• Enterprise Plan: Included
• Professional Plan: Available as an add-on; maximum concurrent memory image sessions may apply depending on tier.

Last Reviewed: 2026-05-26