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detect Agenttesla in memory

yara LOW Yara-Rules
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This rule was pulled from an open-source repository and enriched with AI. Validate in a test environment before deploying to production.
View original rule at Yara-Rules →
Retrieved: 2026-07-03T11:00:00Z · Confidence: medium

Hunt Hypothesis

This hunt targets adversaries utilizing the AgentTesla remote access trojan to establish persistent memory-based footholds within endpoints for credential harvesting and lateral movement. Proactively searching for this behavior in Azure Sentinel is critical because early detection of AgentTesla’s in-memory artifacts allows SOC teams to mitigate silent data exfiltration before it escalates into a broader compromise, despite the rule’s current low severity classification.

YARA Rule

rule Agenttesla_type2 {
          meta:
            description = "detect Agenttesla in memory"
            author = "JPCERT/CC Incident Response Group"
            rule_usage = "memory scan"
            reference = "internal research"
            hash1 = "670a00c65eb6f7c48c1e961068a1cb7fd3653bd29377161cd04bf15c9d010da2 "

          strings:
            $type2db1 = "1.85 (Hash, version 2, native byte-order)" wide
            $type2db2 = "Unknow database format" wide
            $type2db3 = "SQLite format 3" wide
          condition: all of them
}

Deployment Notes

This YARA rule can be deployed in the following contexts:

This rule contains 3 string patterns in its detection logic.

References

False Positive Guidance

Here are 4 specific scenarios where the detect Agenttesla in memory rule may generate false positives in an enterprise environment, along with recommended filters or exclusions:

Original source: https://github.com/Yara-Rules/rules/blob/main/malware/MalConfScan.yar