GoldFinder is a custom HTTP tracer tool written in Go that logs the route a packet takes between a compromised network and a C2 server. It can be used to inform threat actors of potential points of discovery or logging of their actions, including C2 related to other malware. GoldFinder was discovered in early 2021 during an investigation into the SolarWinds Compromise by APT29.[1]
3
TechniquesBottom 12%
3
TacticsBottom 21%
1
Threat groupunranked
1
Campaignunranked
Enterprise ATT&CK only. Any Mobile or ICS rows on the same ATT&CK page are not carried.
GoldFinder performed HTTP GET requests to check internet connectivity and identify HTTP proxy servers and other redirectors that an HTTP request traveled through.2
GoldFinder logged and stored information related to the route or hops a packet took from a compromised machine to a hardcoded C2 server, including the target C2 URL, HTTP response/status code, HTTP response headers and values, and data received from the C2 node.4
Collection11 detection rules
Standing S0597
Reach is how much of ATT&CK this malware touches. Coverage is how well defended each thing it does is, as a median per technique rather than a total — a total would just restate the reach. Each figure is ranked against all 825 ATT&CK software entries only where that population actually spreads. Where most of the population shares one value, a percentile would rank the tie instead of the entity, so the raw value is shown and no rank is claimed.
Reach
Techniques3Bottom 12%
12th percentile · 88% of 825 ATT&CK software entries have more Enterprise techniques.
Tactics3Bottom 21%
21st percentile · 79% of 825 ATT&CK software entries have more tactics spanned.
Threat group161% tie · 22 values
61% of the population shares a single value across only 22 distinct values, so a percentile here would rank the tie, not the entity.
Campaign185% tie · 8 values
85% of the population shares a single value across only 8 distinct values, so a percentile here would rank the tie, not the entity.
Coverage
Rules / technique11medBottom 19%
19th percentile · 81% of 825 ATT&CK software entries have more detection rules per technique.
Tests / technique4med28th pct
28th percentile · 72% of 825 ATT&CK software entries have more atomic tests per technique.
Data comps / technique5med54% tie · 11 values
54% of the population shares a single value across only 11 distinct values, so a percentile here would rank the tie, not the entity.
Mitigations / technique2medTop 9%
91st percentile · 91% of 825 ATT&CK software entries have this many mitigations per technique or fewer.
5 of 8 axes carry an honest rank on this page. Coverage medians are taken across this malware’s 3 Enterprise techniques.
Range
Technique Campaign use over its cumulative rule count.
Adversaries may communicate using application layer protocols associated with web traffic to avoid detection/network filtering by blending in with existing traffic. (...)
This analytic detects the usage of the Utility osascript on a macOS device initiated a network connection lasting longer than 10 minutes (600 seconds). (...)
The following analytic detects the use of known suspicious SSL certificates in any observed event where the SSL_CertFingerprint field is present. (...)
The following analytic detects connections with a high Encrypted Visibility Engine (EVE) threat confidence score, indicating potentially malicious behavior within encrypted traffic. (...)
HTTP request smuggling is a technique for interfering with the way a web site processes sequences of HTTP requests that are received from one or more users. (...)
The following analytic detects HTTP POST requests containing heavily encoded data in the post body, specifically looking for sequences of hex-encoded bytes or base64-encoded strings. (...)
This detection identifies rapid-fire POST request attacks where an attacker sends more than 20 POST requests within a 5-second window, potentially attempting to exploit race conditions or overwhelm request handling. (...)
Detects attempts to exploit a request smuggling technique against IIS that leverages a Windows quirk where requests for reserved Windows device names such as "/con" trigger an early server response before the request body is received. (...)
This Splunk query analyzes web logs to identify and categorize user agents, detecting various types of Remote Monitoring and Mangement applications. (...)
This Splunk query analyzes web access logs to identify and categorize non-browser user agents, detecting various types of security tools, scripting languages, automation frameworks, and suspicious patterns. (...)