AN0927: Analytic 0927
A process/script constructs or references a custom/alphabet translation table (e.g., 64/85/32+ arbitrary chars, XOR/base-N loops) or emits long high-entropy strings that do NOT validate as standard Base64/Hex → shortly after, the same process (or its child) generates outbound traffic with asymmetric bytes_out:bytes_in, fixed-size beacons, or protocol/header mismatches (e.g., Content-Type says JSON but body fails JSON parse / contains non-standard alphabet).
Analyst context for executives and security teams
AN0927 describes a Windows-focused detection analytic for suspicious custom encoding or obfuscation followed by unusual outbound network behavior. The business value is that this pattern can help defenders spot activity that is trying to hide data or communications from normal content inspection, especially when the data does not match standard Base64 or Hex formats and is followed by beacon-like or protocol-inconsistent traffic.
Executive priority
Treat this as a validation point for SOC and incident response readiness rather than a standalone risk finding. Leaders should ask whether Windows endpoint telemetry, script/process visibility, and network inspection are correlated well enough to connect suspicious string construction with outbound traffic behavior. This matters for operational resilience because the analytic depends on joining host-side execution evidence with network-side anomalies; gaps in either source can leave leadership with weak evidence during incident triage, audit review, or control effectiveness discussions.
Technical view
For Windows environments, validate whether detection engineering can correlate a process or script that constructs or references custom alphabet/translation tables, XOR or base-N style loops, or long high-entropy strings that fail standard Base64/Hex validation, with subsequent outbound traffic from the same process or child process. Network-side indicators called out by the ATT&CK object include asymmetric bytes_out to bytes_in, fixed-size beaconing, and protocol or header mismatches such as a JSON Content-Type where the body fails JSON parsing or contains a non-standard alphabet. Because no official detection logic is supplied, teams should treat this as an analytic design pattern requiring local tuning and testing.
Likely telemetry
- Windows process creation and parent-child process lineage
- Script execution telemetry where available
- Command-line and process metadata
- Endpoint observations of high-entropy or non-standard encoded strings where collected
- Network connection metadata tied back to process identity
Detection direction
- Validate that host and network telemetry can be correlated by process, child process, user, host, and time window.
- Tune for combinations of suspicious encoding behavior plus outbound traffic anomalies rather than either signal alone.
- Confirm parsers can distinguish standard Base64 or Hex from non-standard alphabets to reduce noisy matches.
- Review false positives from legitimate compression, serialization, telemetry agents, backup tools, development tools, or proprietary protocols that may emit high-entropy strings or non-JSON payloads.
- Check blind spots where encrypted traffic, limited script logging, missing process lineage, or lack of application-layer parsing prevents confirmation of the described behavior.
Mitigation priorities
- Prioritize visibility first: ensure Windows process lineage, script activity, and outbound network metadata are available to the SOC.
- Improve correlation between endpoint and network controls so process-originated outbound activity can be investigated quickly.
- Apply least-privilege and egress governance where appropriate to reduce unnecessary outbound communication paths from Windows systems.
- Use allowlists or baselines for known applications that legitimately use custom encodings or proprietary protocols.
- Document telemetry coverage and analytic assumptions as compliance and incident-response evidence, especially where content inspection is limited.
Analyst notes and limits
This is a detection analytic object, not a technique or procedure. The supplied ATT&CK fields provide a concise behavioral description but no official detection pseudocode, no tactics, and no relationships to malware, groups, campaigns, or techniques. The strongest defensive use is as a coverage and correlation test across Windows endpoint and network telemetry.
Assessment is limited to the supplied STIX fields, external reference, and absence of relationship context. No claim can be made about active exploitation, adversary attribution, impact, prevalence, or guaranteed detection. Local environment telemetry, protocol visibility, encryption constraints, and known-good application behavior are required before operationalizing this analytic.
Analytic 0927
A process/script constructs or references a custom/alphabet translation table (e.g., 64/85/32+ arbitrary chars, XOR/base-N loops) or emits long high-entropy strings that do NOT validate as standard Base64/Hex → shortly after, the same process (or its child) generates outbound traffic with asymmetric bytes_out:bytes_in, fixed-size beacons, or protocol/header mismatches (e.g., Content-Type says JSON but body fails JSON parse / contains non-standard alphabet).
How security teams should use this page
Treat this object as behavior context, not an attribution claim. Validate the related groups, software, data sources, and mitigations against official ATT&CK relationships and your own telemetry before making control-coverage decisions.
All related ATT&CK context
No relationships are available in the current normalized data for this object.
Object version and sync metadata
The fields below describe the current mirrored snapshot. When Glexia retains multiple ATT&CK source imports, you can open the table to compare the same object across releases (hashes and MITRE timestamps). For MITRE’s own release notes and roadmap, see ATT&CK resources — Updates .
Imported snapshots across ATT&CK releases (1)
| Release | Bundle imported | Object version | Modified | Status | Raw hash |
|---|---|---|---|---|---|
| 19.1 | 1.0 | Current bundle | ab41a003b76c… |
Mirrored ATT&CK source object
The raw object is retained through the mirrored ATT&CK source bundle and object hash. The raw endpoint returns the exact object from the mirrored bundle when available.
External references and citations
MITRE external references are preserved separately from Glexia analysis so citations remain traceable to their original source records.
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[1]
mitre-attack AN0927Open source URL
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