Security teams should start with file and persistence artefacts that are unusual for the operating system, then translate them into repeatable endpoint queries. In practice, that means monitoring suspicious directories, startup mechanisms, and registry paths, and enriching results with usernames, group names, timestamps, and hashes so analysts can quickly confirm whether the activity is likely malicious.
Use endpoint telemetry to start with what malware can leave behind
The practical value of endpoint telemetry is that it lets hunters look for durable artefacts instead of relying on a single signature or filename. On Linux, macOS, and Windows, malware that persists usually has to touch startup mechanisms, scheduled execution paths, or writable locations that are atypical for normal software. Good hunting starts by turning those platform-specific behaviours into repeatable queries over file creation, modification, and process context.
That means treating “unusual files” as a behavioural problem, not just a file-location problem. Focus on directories and paths that are commonly abused for persistence, then correlate them with the process that created them, the user context, and whether the write happened from an interactive session, script, installer, or parent process that would normally not manage persistence.
Across platforms, the most useful triage fields are the same even when the artefact paths differ: path, timestamp, hash, signer or package provenance where available, parent process, user, and the first-seen age of the file. Those details make it easier to separate a suspicious persistence file from a legitimate application updater, login item, cron job, or service component.
Translate platform artefacts into repeatable hunting logic
Effective hunting depends on mapping the operating-system mechanism to the query, rather than memorising one-off indicators. On Windows, that often means registry run keys, services, scheduled tasks, startup folders, DLL search abuse, and dropped binaries in writable paths. On Linux, it means cron, systemd units, init scripts, shell profile changes, and writes into home or temporary directories that later become execution points. On macOS, it means LaunchAgents, LaunchDaemons, login items, plist changes, and modified application support paths.
The strongest hunts look for combinations, not isolated artefacts. A new file in a suspicious path becomes much more meaningful when it is paired with an unexpected process lineage, a recent privilege change, or repeated execution after reboot or user logon. If telemetry includes command lines and child-process creation, use that context to distinguish installer activity from persistence creation.
Build queries that can be reused by normalising around behaviours: “new executable written to user-writable location”, “persistence artefact created by office, browser, archive, or scripting process”, “startup object modified shortly after archive extraction”, and “hash appears on multiple endpoints with different names or paths”. This approach is more durable than chasing file names alone and works better when malware changes packaging or renames itself.
Telemetry value increases sharply when you can chain events. A file write, followed by a registry or startup-path modification, followed by repeated execution from that same location is a much stronger pattern than any one event in isolation. That is the difference between simple file review and actual endpoint hunting.
Risk and Threat Considerations
Malware that creates unusual files and persistence is dangerous because the file is often only the first visible step in an access path that is meant to survive reboot, user logon, or process restart. The main risk is not the artefact itself, but the fact that it can preserve execution and make later detection much harder if telemetry is incomplete or not correlated across the lifecycle.
Failure mechanism: Adversaries abuse writable locations, startup mechanisms, and execution hooks to establish persistence, then hide behind ordinary-looking file activity, legitimate parent processes, or delayed execution. If endpoint telemetry does not capture creation context, path normalisation, and repeated execution, the persistence chain can look like harmless file churn.
Impact: Missed persistence increases dwell time, enables repeat compromise after remediation, and can allow the same payload to reappear across multiple hosts under new names. In mixed Linux, macOS, and Windows estates, inconsistent telemetry also creates blind spots that attackers can exploit to move between operating-system-specific persistence methods.
Standards & Framework Alignment
This section maps relevant standards and security frameworks to the operational risks and controls described in this guidance.
CIS Controls v8 provides the primary governance reference for this topic.
| Framework | Control / Reference | Relevance |
|---|---|---|
| CIS Controls v8 | CIS Control 8 — Audit Log Management | Endpoint telemetry hunting depends on collecting and correlating file and process events. |
| CIS Control 10 — Malware Defenses | The question is specifically about hunting malware artefacts and persistence behaviour. | |
| CIS Control 4 — Secure Configuration of Enterprise Assets and Software | Persistence often abuses startup paths, services, and writable configuration locations. | |
| Recommendation — Centralize endpoint logs and retain process, file, and startup-event records for correlation. Monitor for malicious file activity and persistence indicators across endpoints. Harden startup locations and configuration paths that malware commonly uses for persistence. | ||
Practitioner Guidance
What to prioritise: Build hunts around persistence points first, then unusual file locations, because a file only becomes operationally important when it can be executed again. Prioritise telemetry that shows file creation plus process lineage plus follow-on execution, not just isolated filesystem events.
What to verify: Confirm whether the file path is expected for that host class, whether the creating process normally writes there, and whether the same hash or command line appears on other endpoints. If the artefact is only suspicious because of location, validate against the platform’s normal software-update and login behaviour before escalating.
Practitioner takeaway: The best hunts use endpoint telemetry to prove persistence mechanics, not just to spot odd filenames, because the repeatability of the behaviour is what separates noise from compromise.
Related resources from NHI Mgmt Group
- How should security teams implement endpoint protection when they need visibility across Windows, macOS, Linux, and mobile devices?
- How can teams decide whether to centralise developer machine security controls across Linux, macOS, and Windows?
- How should security teams monitor GitHub Actions runners across Linux, Windows, and macOS without changing workflow logic?
- How should security teams use endpoint and identity telemetry to reduce access risk across hybrid environments?
Deepen Your Knowledge
Reviewed and updated by the NHIMG editorial team on September 20, 2026.
NHI Mgmt Group — the #1 independent authority on Non-Human Identity, IAM, and Agentic AI security. nhimg.org
