Trojan.Kryptik.FST
Threat Scorecard
EnigmaSoft Threat Scorecard
EnigmaSoft Threat Scorecards are assessment reports for different malware threats which have been collected and analyzed by our research team. EnigmaSoft Threat Scorecards evaluate and rank threats using several metrics including real-world and potential risk factors, trends, frequency, prevalence, and persistence. EnigmaSoft Threat Scorecards are updated regularly based on our research data and metrics and are useful for a wide range of computer users, from end users seeking solutions to remove malware from their systems to security experts analyzing threats.
EnigmaSoft Threat Scorecards display a variety of useful information, including:
Popularity Rank: The ranking of a particular threat in EnigmaSoft’s Threat Database.
Severity Level: The determined severity level of an object, represented numerically, based on our risk modeling process and research, as explained in our Threat Assessment Criteria.
Infected Computers: The number of confirmed and suspected cases of a particular threat detected on infected computers as reported by SpyHunter.
See also Threat Assessment Criteria.
| Popularity Rank: | 27,328 |
| Threat Level: | 80 % (High) |
| Infected Computers: | 1 |
| First Seen: | June 23, 2026 |
| Last Seen: | June 23, 2026 |
| OS(es) Affected: | Windows |
Trojan.Kryptik.FST is a heuristic detection assigned to a heavily obfuscated 64-bit Windows trojan. The label belongs to the long-running Kryptik detection family, a generic classification used across the security industry for packed and disguised trojans whose real purpose is deliberately hidden from analysts and signature engines alike.
The specific sample analyzed for this report is a large Go-language binary carrying a code-signing certificate that does not validate as trusted. Because Trojan.Kryptik.FST is a wrapper-style detection rather than a single fixed payload, treat any hit as a serious compromise and remediate it immediately.
Table of Contents
What Is Trojan.Kryptik.FST?
The Kryptik name (most widely associated with ESET's Win32/Kryptik and Win64/Kryptik signatures, and echoed by other vendors as Trojan.Kryptik) is not the name of one discrete piece of malware. It is a heuristic verdict that describes how a file is built and hidden rather than what it ultimately does. Files flagged this way share a common trait: they use packing, encryption, anti-analysis logic, and code obfuscation to defeat signature-based scanning. Underneath that obfuscation, the actual payload can be almost anything, from an information stealer or clipboard hijacker to a backdoor, downloader, or loader for a follow-on family.
That generic nature is reflected directly in the analysis data for this sample. Its strongest code-similarity matches are to other Kryptik variants (Kryptik.VDH and Kryptik.BTE), followed by CoinStealer and Rozena clusters. Rozena is a well-documented shellcode/backdoor lineage historically tied to Metasploit-style Meterpreter payloads, and CoinStealer points toward cryptocurrency-theft behavior. These are similarity signals, not a confirmed lineage, but they are consistent with the Kryptik pattern of wrapping stealer or backdoor code inside an evasive shell. The .FST suffix is simply the variant identifier for this specific obfuscated cluster.
How It Spreads / Distribution
Kryptik-class trojans do not rely on a single delivery method; they ride whatever distribution channel the operator prefers. The most consistently reported vectors across public reporting are phishing emails with malicious attachments or links, drive-by downloads from compromised or malicious websites, and "cracked" software, keygens, and pirated media bundles. Exploit kits and malvertising redirects are also common, and loader campaigns frequently chain Kryptik payloads behind an initial script or document downloader.
The analyzed sample is a large file (roughly 3.3 MB) built in Go and shipped as a DLL. Go binaries statically bundle their runtime, which inflates file size and helps the payload blend in with legitimate large applications. A DLL form factor also favors execution via a legitimate host process (for example through rundll32.exe, DLL side-loading, or injection), which lets the malware run without an obvious standalone executable that a user would recognize as suspicious.
Technical Analysis & Behavior
Automated sandbox analysis of the representative sample surfaced a compact but telling behavioral profile. The dominant flagged behavior is direct system-call use (syscall_use). Invoking Windows syscalls directly, rather than through the documented Win32 API, is a deliberate evasion technique: it bypasses the userland API hooks that many endpoint and sandbox products rely on to observe malicious activity. This is a hallmark of modern evasive loaders and is entirely in keeping with the Kryptik obfuscation philosophy.
The file's structural traits reinforce that picture. It is a 64-bit (x64) DLL written in Go with a large appended overlay. Overlays are extra data attached beyond the formal end of the PE image and are a classic hiding spot for encrypted second-stage payloads, configuration blobs, or bundled resources. The analysis also flagged twelve notable PE header characteristics, indicating a binary whose structure diverges enough from a clean, ordinary executable to draw heuristic attention. No packer was positively identified by name, which is common for Go malware and custom crypters that do not match known packer signatures.
Notably, during the observed execution window the sample recorded zero registry modifications and zero file modifications. That should not be read as "harmless." A near-silent run is itself a red flag for evasive malware: samples that detect virtualization, debuggers, or an analysis sandbox frequently withhold their real behavior, and syscall-based loaders often stage their damaging activity in memory or defer it until specific conditions are met. As always, these values reflect one analyzed sample; specific indicators rotate between builds.
Indicators of Compromise
The following indicators come from the single representative sample examined for this report. They are useful for hunting an exact match but will not catch every variant, because Kryptik operators recompile and re-pack frequently, changing every hash. Treat these as a starting point, not an exhaustive block list.
- SHA-256: B68C10AEC5BD9BF2D0E9824F9567A15DAE7AA324611FBD3CA0BFF6EEEA16FACC
- SHA-1: dcc8ef83e4e3d049623a9332af88ec089668b257
- MD5: 874d95b5c266401f5d397312ee0d604f
- File size: 3,372,168 bytes (~3.3 MB)
- File type: 64-bit Go DLL with a large overlay
- Authenticode signer: "ambito.com" — a signature is present but did not validate as trusted, so it should be treated as untrusted/spoofed rather than as evidence of a legitimate publisher.
No network indicators (C2 IP addresses, domains, or URLs) were captured for this sample, so none are asserted here. The disclaimer bears repeating: specific hashes, signer strings, and overlay contents rotate between builds.
Detection Heuristics
Because Kryptik is itself a heuristic verdict, it is worth understanding why engines flag files like this. Detection typically leans on a blend of signals rather than a single string match. PE-structure heuristics fire on the anomalous header characteristics and the large overlay. Behavioral heuristics key on direct syscall invocation and on the absence of the benign activity a legitimate application of this size would normally perform. Code-similarity and machine-learning classifiers place the binary near known Kryptik, CoinStealer, and Rozena clusters. Finally, trust heuristics weigh the invalid code signature: a certificate that fails validation, attributed here to "ambito.com," pushes the reputation score sharply negative. Any one of these on its own might be inconclusive, but together they produce a high-confidence malicious verdict.
Digital Forensics
When hunting Trojan.Kryptik.FST on a host, focus on the artifacts consistent with an evasive Go DLL loader. Look for large (multi-megabyte) DLLs in user-writable locations such as %AppData%, %LocalAppData%, %Temp%, and %ProgramData%, especially files whose Authenticode signature fails validation or is attributed to an unexpected signer. Examine process trees for legitimate Windows binaries (for example rundll32.exe) loading unfamiliar DLLs, and for processes that make direct syscalls or exhibit injected/unbacked executable memory regions.
The analyzed sample logged no on-disk registry or file modifications during observation, so persistence for a given variant may be memory-resident, deferred, or established only outside a sandbox. Still, check the usual persistence anchors as a matter of routine: Run/RunOnce registry keys, scheduled tasks, services, and startup folders. Preserve memory images where possible, since syscall-based loaders often reveal their true payload only in RAM. Because indicators rotate, prioritize behavioral and structural hunting (unsigned/invalid-signed large Go DLLs, direct-syscall behavior) over chasing individual hashes.
Symptoms of Infection
Kryptik infections are engineered to be quiet, so overt symptoms may be subtle or absent. Possible signs include unexplained system slowdowns or high CPU usage, unfamiliar processes or DLLs in memory, security software being disabled or throwing repeated warnings about a specific file, and unexpected outbound network connections. If the wrapped payload is a stealer or clipboard hijacker, victims may notice account compromises, altered cryptocurrency wallet addresses during copy/paste, or credentials used without authorization. The safest assumption on any confirmed detection is that data may have been exposed.
How to Remove Trojan.Kryptik.FST
Because the underlying payload is unknown and can include credential- or crypto-stealing capabilities, remediate promptly and assume potential data exposure.
- Run a full anti-malware scan. Use a reputable, up-to-date security tool such as SpyHunter and perform a complete (full) system scan, not a quick scan, so packed DLLs in
AppData,Temp, andProgramDataare inspected. Quarantine and remove everything it flags, then reboot and scan again to confirm the system is clean. - Boot into Safe Mode with Networking. If the trojan resists removal or interferes with your security software, restart into Safe Mode (hold Shift while choosing Restart > Troubleshoot > Advanced options > Startup Settings) and run the full scan again from there, where the malware is less likely to be active.
- Clean your browsers in case a stealer payload tampered with them:
- Google Chrome: Settings > Reset settings > "Restore settings to their original defaults," then review Extensions and remove anything unfamiliar.
- Mozilla Firefox: Help > More troubleshooting information > "Refresh Firefox," then check Add-ons and Themes.
- Microsoft Edge: Settings > Reset settings > "Restore settings to their default values," then review Extensions.
- Android: Boot into Safe Mode, uninstall any recently added or unknown apps from Settings > Apps, and run a mobile security scan; factory reset as a last resort.
- Manual cleanup (advanced users). End suspicious processes, delete the identified malicious DLL and any large invalid-signed files in user-writable folders, and remove associated startup entries, scheduled tasks, or services. Proceed carefully — deleting the wrong system file can destabilize Windows.
- Post-cleanup hygiene. From a known-clean device, change passwords for important accounts, enable multi-factor authentication, and if cryptocurrency wallets were present, move funds to new wallets. Keep Windows and all applications fully patched.
Conclusion
Trojan.Kryptik.FST is best understood as an evasive wrapper, not a single fixed payload. The analyzed sample is a large, Go-built 64-bit DLL that hides behind a big overlay, carries an invalid code signature attributed to "ambito.com," and leans on direct system calls to slip past monitoring. Its closest code relatives span other Kryptik variants along with CoinStealer and Rozena clusters, underscoring that the true payload could be a stealer, backdoor, or loader. Given that uncertainty and the potential for data theft, any detection should be treated as a genuine compromise: run a full scan with a trusted tool such as SpyHunter, hunt for the behavioral artifacts described above, and rotate credentials once the host is clean.
Analysis Report
General information
| Family Name: | Trojan.Kryptik.FST |
|---|---|
| Signature status: | Self Signed |
Known Samples
Known Samples
This section lists other file samples believed to be associated with this family.|
MD5:
874d95b5c266401f5d397312ee0d604f
SHA1:
dcc8ef83e4e3d049623a9332af88ec089668b257
SHA256:
B68C10AEC5BD9BF2D0E9824F9567A15DAE7AA324611FBD3CA0BFF6EEEA16FACC
File Size:
3.37 MB, 3372168 bytes
|
Windows Portable Executable Attributes
- File doesn't have "Rich" header
- File doesn't have debug information
- File doesn't have resources
- File has exports table
- File has TLS information
- File is 64-bit executable
- File is either console or GUI application
- File is GUI application (IMAGE_SUBSYSTEM_WINDOWS_GUI)
- File is Native application (NOT .NET application)
- File is not packed
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- IMAGE_FILE_DLL is not set inside PE header (Executable)
- IMAGE_FILE_EXECUTABLE_IMAGE is set inside PE header (Executable Image)
Digital Signatures
Digital Signatures
This section lists digital signatures that are attached to samples within this family. When analyzing and verifying digital signatures, it is important to confirm that the signature’s root authority is a well-known and trustworthy entity and that the status of the signature is good. Malware is often signed with non-trustworthy “Self Signed” digital signatures (which can be easily created by a malware author with no verification). Malware may also be signed by legitimate signatures that have an invalid status, and by signatures from questionable root authorities with fake or misleading “Signer” names.| Signer | Root | Status |
|---|---|---|
| ambito.com | ambito.com | Self Signed |
File Traits
- big overlay
- dll
- golang
- x64
Block Information
Block Information
During analysis, EnigmaSoft breaks file samples into logical blocks for classification and comparison with other samples. Blocks can be used to generate malware detection rules and to group file samples into families based on shared source code, functionality and other distinguishing attributes and characteristics. This section lists a summary of this block data, as well as its classification by EnigmaSoft. A visual representation of the block data is also displayed, where available.| Total Blocks: | 4,136 |
|---|---|
| Potentially Malicious Blocks: | 54 |
| Whitelisted Blocks: | 4,082 |
| Unknown Blocks: | 0 |
Visual Map
? - Unknown Block
x - Potentially Malicious Block
Similar Families
Similar Families
This section lists other families that share similarities with this family, based on EnigmaSoft’s analysis. Many malware families are created from the same malware toolkits and use the same packing and encryption techniques but uniquely extend functionality. Similar families may also share source code, attributes, icons, subcomponents, compromised and/or invalid digital signatures, and network characteristics. Researchers leverage these similarities to rapidly and effectively triage file samples and extend malware detection rules.- CoinStealer.CC
- Kryptik.BTE
- Kryptik.VDH
- Rozena.DDC
- Rozena.MC
Windows API Usage
Windows API Usage
This section lists Windows API calls that are used by the samples in this family. Windows API usage analysis is a valuable tool that can help identify malicious activity, such as keylogging, security privilege escalation, data encryption, data exfiltration, interference with antivirus software, and network request manipulation.| Category | API |
|---|---|
| Syscall Use |
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