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name, description, domain, subdomain, tags, version, author, license, mitre_attack, d3fend, references
name description domain subdomain tags version author license mitre_attack d3fend references
analyzing-api-call-traces Analyzes API call traces from a sandbox or API monitor (JSON) to group calls by category, reconstruct high-level behaviors (process injection, file drops, network, crypto), and flag suspicious call sequences. Activates for requests to analyze an API trace, interpret sandbox API logs, or identify behavior from Win32/Native API calls. cybersecurity malware-analysis
malware-analysis
dynamic-analysis
api-trace
winapi
sandbox
1.0.0 analyst-ai-pack Apache-2.0
T1106
T1055
T1027
D3-PSA
D3-SDA
MITRE ATT&CK T1106 Native API — https://attack.mitre.org/techniques/T1106/
Windows API Index — https://learn.microsoft.com/windows/win32/apiindex/windows-api-list

Analyzing API Call Traces

When to Use

  • You have a JSON API trace (CAPE/Cuckoo "apistats"/calls, API Monitor export) from a detonation.
  • You need to translate raw API calls into high-level behaviors and flag suspicious sequences (e.g., VirtualAllocEx → WriteProcessMemory → CreateRemoteThread).

Do not use this as a substitute for detonation — it consumes an existing trace produced in an isolated sandbox.

Prerequisites

  • A JSON API trace with at least an API name per call (and optionally arguments).

Safety & Handling

  • Consume traces only; never execute the sample to generate one outside a sandbox.

Workflow

Step 1: Group calls by category

python scripts/analyst.py classify trace.json

Buckets calls into process, memory, file, registry, network, crypto, and synchronization.

Step 2: Detect behavior signatures

Matches ordered API sequences that indicate techniques — remote injection, hollowing, self-deletion, dynamic API resolution (LoadLibrary/GetProcAddress bursts).

Step 3: Prioritize and report

Rank detected behaviors by severity and map each to ATT&CK.

Validation

  • Each API call is categorized; unknown APIs are reported, not dropped silently.
  • Injection-style sequences are detected only when the ordered prerequisites are present.
  • Detected behaviors map to ATT&CK techniques.

Pitfalls

  • Flagging individual benign APIs out of context — the sequence matters.
  • Assuming call order in the JSON equals execution order without a timestamp/index.
  • Ignoring failed calls (non-zero error) that never actually executed the behavior.

References