skills/detecting-dll-sideloading-attacks/SKILL.md
Detect DLL side-loading attacks where adversaries place malicious DLLs alongside legitimate applications to hijack execution flow for defense evasion.
npx skillsauth add mukul975/anthropic-cybersecurity-skills detecting-dll-sideloading-attacksInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
3 of 9 scanners reported clean
Some scanners were skipped, did not run, or reported a non-clean status. Review each row below.
| Concept | Description | |---------|-------------| | T1574.002 | DLL Side-Loading | | T1574.001 | DLL Search Order Hijacking | | T1574.006 | Dynamic Linker Hijacking | | T1574.008 | Path Interception by Search Order Hijacking | | DLL Search Order | Windows DLL loading priority path | | Side-Loading | Placing malicious DLL where legitimate app loads it | | Phantom DLL | DLL that legitimate apps try to load but does not exist | | DLL Proxying | Malicious DLL forwarding calls to legitimate DLL |
| Tool | Purpose | |------|---------| | Sysmon | Event ID 7 DLL load monitoring | | CrowdStrike Falcon | DLL load detection with process context | | Microsoft Defender for Endpoint | DLL load anomaly detection | | Process Monitor | Real-time DLL load tracing | | DLL Export Viewer | Verify DLL export functions | | Sigcheck | Digital signature verification | | pe-sieve | PE analysis for proxied DLLs |
Hunt ID: TH-SIDELOAD-[DATE]-[SEQ]
Technique: T1574.002
Host Application: [Legitimate signed executable]
Sideloaded DLL: [Malicious DLL name and path]
Expected DLL Path: [Where DLL should legitimately be]
DLL Signed: [Yes/No]
App Location: [Expected/Anomalous]
Host: [Hostname]
Risk Level: [Critical/High/Medium/Low]
data-ai
Detect adversary lateral movement across networks using Splunk SPL queries against Windows authentication logs, SMB traffic, and remote service abuse.
testing
Identifies lateral movement techniques in enterprise networks by analyzing authentication logs, network flows, SMB traffic, and RDP sessions using Zeek, Velociraptor, and SIEM correlation rules to detect attackers moving between systems.
tools
Detect Kerberoasting attacks by monitoring for anomalous Kerberos TGS requests targeting service accounts with SPNs for offline password cracking.
development
Implement User and Entity Behavior Analytics using Elasticsearch/OpenSearch to build behavioral baselines, calculate anomaly scores, perform peer group analysis, and detect insider threat indicators such as data exfiltration, privilege abuse, and unauthorized access patterns.