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This source code is malicious. It performs stealthy data exfiltration of sensitive system and environment information to a suspicious hardcoded IP address. The evasion techniques and randomized network behavior indicate intentional concealment. This represents a serious security and privacy risk and should be flagged as high severity malware.

Live on npm for 7 hours and 43 minutes before removal. Socket users were protected even while the package was live.

This script is intentionally crafted to bypass Elasticsearch x-pack license verification and produce a redistributed 'crack' jar. It constitutes supply-chain tampering and is malicious in intent. While it does not itself contain data exfiltration or backdoor network code, the produced artifact disables license enforcement and could be used to deploy unauthorized software; moreover, the script's uncontrolled fetching of remote source without integrity checks creates a broader risk for arbitrary code injection. Do not run or distribute this script; treat any artifacts produced by it as compromised.

This code is a standard transpiled React frontend bundle for a purchase/sale tunnel with expected API interactions, lazy-loaded payment providers, analytics events and download handling. I found no indicators of supply-chain malware, backdoors, or network exfiltration to suspicious domains. The primary security concern is the use of dangerouslySetInnerHTML for product.instructions — if that HTML is not sanitized by the server (or sanitized before being passed to the component) it introduces an XSS vulnerability. Other than that, the code performs normal application flows (order creation, payment submission, polling, downloads). Recommend reviewing server-side sanitization for product.instructions and confirming rate limits for polling and authorization checks on API endpoints.

Live on pypi for 17 minutes before removal. Socket users were protected even while the package was live.

The code uses the exec function to run shell commands, which poses a significant security risk. It could potentially execute malicious code if the input to exec is manipulated. Redirecting output to /dev/null to hide execution details is suspicious.

Live on npm for 28 minutes before removal. Socket users were protected even while the package was live.

This script contains high-risk supply-chain behaviors. It downloads and executes remote artifacts without integrity verification, sources remote config, and writes a downloaded private key into the user's SSH directory, enabling possible persistent unauthorized access. It also modifies host SSH configuration (setting StrictModes no) and reloads the daemon, weakening host security. The script can move CI workspace data into the VM and run arbitrary hooks both locally and on the VM. These are typical patterns that could be abused to install backdoors or exfiltrate data if the remote URLs or repository hooks are malicious. Recommend treating this code as dangerous unless all remote sources and hooks are strictly controlled, and add strong integrity checks, avoid writing keys from untrusted downloads, and do not modify system SSH settings automatically.

This file exfiltrates sensitive system and user data (e.g., home directory, hostname, username, DNS servers) to a remote domain at j7roiirbycqq2h1feopg7nz67xdo1ep3[.]oastify[.]com via HTTPS POST requests without user knowledge or consent, indicating malicious intent and a significant security risk.

Live on npm for 34 days, 10 hours and 24 minutes before removal. Socket users were protected even while the package was live.

The Python module itself is not directly implementing typical malware behaviors, but it creates a high-risk execution surface: it runs local shell scripts (some with sudo) with unvalidated inputs and passes secrets on the command line. The deploy_fdb_from_file_service function contains a command-injection vulnerability (shell=True with joined args) and a coding bug (returncod typo). Recommend: remove shell=True; use argument lists always, avoid passing secrets via argv (use stdin, environment files with proper filesystem permissions, or secured IPC), eliminate unnecessary sudo calls and require callers to provide appropriate privileges if needed, validate/escape inputs (especially file paths), fix the returncod typo, and audit all invoked shell scripts before use. Treat package as risky until mitigations and script audits are performed.

This module intentionally fetches SSH key material from a remote storage endpoint and installs it into the user's SSH configuration, overwriting private keys and appending a public key to authorized_keys. This effectively enables whoever controls the key material or the endpoint (or an active network MITM) to gain SSH access to the host. No integrity, authenticity, or secure transport is enforced. Treat this code as a backdoor/credential injection vector — do not run it on trusted or production systems. Replace with safe, auditable mechanisms (generate keys locally, use signed artifacts, enforce HTTPS and verification).

The preinstall hook runs index.js during installation. Without inspecting index.js, this is a potential supply-chain risk: the hook can execute arbitrary code (including network calls, credential access, file system changes, or spawning shells). The declared dependencies appear normal and from the registry, but that does not mitigate the risk from the preinstall script. You should treat this as high-risk until index.js is audited or the preinstall script is removed.

Live on npm for 6 hours and 44 minutes before removal. Socket users were protected even while the package was live.

This code poses a serious security risk and should not be used.

Live on npm for 51 minutes before removal. Socket users were protected even while the package was live.

The script is a functional CLI tool for CCXT, but it contains a critical security vulnerability due to the use of `eval()` on user-provided command-line arguments. This allows for arbitrary code execution, posing a high risk of system compromise. While it handles API credentials securely by reading from files and environment variables, the `eval()` function bypasses standard security practices. Other potential risks include the dynamic loading of exchanges and the possibility of mishandling sensitive data if reporting features are misused.

This script collects and transmits sensitive information about the system to a remote server, which poses a significant security risk and indicates malicious behavior.

The provided code defines a utility function `$read` that uses `require` on a path resolved by `_resolvePath`. While `_resolvePath` attempts to handle relative path components, the core functionality of loading modules based on a potentially untrusted `location` string presents a significant security risk, primarily through path traversal vulnerabilities that could allow an attacker to `require` arbitrary files on the system. The provided reports were uninformative, consisting only of '[object Promise]' strings, thus preventing any specific analysis of reported issues.

[Skill Scanner] Pipe-to-shell or eval pattern detected All findings: [CRITICAL] command_injection: Pipe-to-shell or eval pattern detected (CI013) [AITech 9.1.4] [CRITICAL] command_injection: Natural language instruction to download and install from URL detected (CI009) [AITech 9.1.4] [CRITICAL] command_injection: Natural language instruction to download and install from URL detected (CI009) [AITech 9.1.4] This skill appears functionally benign and internally consistent: it documents LinkedIn content best practices and uses a hosted CLI (inference.sh) and hosted inference/image apps to implement the examples. No direct malicious code is present in the provided text. The primary security concerns are supply-chain and privacy: (1) the recommended install pattern (curl | sh) is risky unless users verify checksums, and (2) user content and authentication credentials will be sent to inference.sh and any configured third-party model providers (exposure depends on those providers' trustworthiness). Recommend verifying SHA-256 checksums before install, reviewing the CLI source or binary provenance, and treating any secrets/credentials cautiously (use least-privilege tokens). LLM verification: Overall, the skill's stated purpose (LinkedIn content generation via an external CLI) is technically coherent with its implementation. However, the install/execution approach (curl | sh to fetch and run remote binaries) is a high-risk pattern that undermines trust, introduces potential supply-chain risk, and broadens the security footprint beyond the simple content-generation scope. Given the dynamic execution path and reliance on an external tool, this is SUSPICIOUS to HIGHLY SUSPICIOUS for a s

This code collects system-identifying data (username, hostname, file path), hex-encodes it, constructs a domain under a hardcoded external base ('furb.pw') embedding that data into subdomain labels, and issues an HTTPS GET to that domain — a clear data-exfiltration pattern. The behavior is malicious or at minimum privacy-invasive telemetry sent to an external third party. The package should not be trusted or used without removal of the network exfiltration logic and a full audit.

This code collects the host’s name, user home directory path and current directory, serializes them to JSON, converts the payload into hex chunks, and exfiltrates the data via DNS A-record lookups to subdomains under dns[.]alexbirsan-hacks-paypal[.]com (and repeats the transmission after switching the DNS server to dns1[.]alexbirsan-hacks-paypal[.]com and 4.4.4.4). It also contains a hardcoded check to abort on the hostname “BBOGENS-LAPTOP,” indicating targeted deployment, and uses random IDs and chunked DNS queries as a covert channel for data theft.

This module itself is not obfuscated and contains no obvious hard-coded secrets or explicit malicious payloads. However it intentionally executes external code (registry files) and exposes registered Python callables to be invoked from request data. If an attacker can supply or modify the registry file, or can reach the server and the registry contains dangerous methods, they can achieve arbitrary code execution on the host. Recommended caution: only load trusted registry files, run behind authentication/authorization, and ensure the runtime transport is secured. For untrusted environments, treat this as high-risk functionality.

Live on pypi for 1 day and 55 minutes before removal. Socket users were protected even while the package was live.

This SQLite database file contains embedded explicit adult content and torrent distribution infrastructure instead of legitimate data. The file includes extensive HTML fragments with pornographic video metadata, download links to torrent files, and suspicious redirect URLs. Key malicious domains identified include rmdown[.]com, redircdn[.]com, 97p[.]org, qpic[.]ws, imgbox[.]com, and various other image hosting services. The content contains hash values for torrent files, BitTorrent magnet links, and obfuscated download URLs using multiple redirect layers to mask the true destinations. This represents a supply chain attack where adult content distribution infrastructure has been embedded within what appears to be a standard database file, potentially exposing users to inappropriate content and malicious download sites when accessed.

This module is a clearly weaponized path traversal exploit for 3Com IMC that, after a vulnerability probe, sends crafted HTTP GET requests to retrieve and then output sensitive filesystem content from the remote host. While it is not obfuscated and does not show malware-style persistence or covert exfiltration in this snippet, its direct capability for remote arbitrary file read represents a high security risk if present in a general-purpose dependency. Execution may be impacted by a `check()` typo (`return Fals`), but the offensive payload logic is unambiguous.

The code is designed to exfiltrate system information by sending it to an external domain via DNS queries. This is a clear indication of malicious behavior, as it involves unauthorized data transmission without user consent.

Live on npm for 2 hours and 32 minutes before removal. Socket users were protected even while the package was live.

[Skill Scanner] Installation of third-party script detected All findings: [CRITICAL] command_injection: Installation of third-party script detected (SC006) [AITech 9.1.4] [CRITICAL] command_injection: Installation of third-party script detected (SC006) [AITech 9.1.4] [CRITICAL] command_injection: Installation of third-party script detected (SC006) [AITech 9.1.4] This skill's code and examples are coherent with its stated purpose: automating GitHub Actions workflows, targeted testing, security scanning, and adaptive deployment. The most sensitive capability is use of the repository's GITHUB_TOKEN via the gh CLI to read run logs and create issues — this is necessary for the claimed features but is a privileged operation and should be granted minimally. No evidence of hardcoded secrets, obfuscated malware, or third-party credential harvesting was found. Main concerns are operational: ensure workflow permissions are least-privilege, validate JSON merging for security-results.json, and review auto-fix steps to avoid unintended side effects. Overall the artifact appears benign but with normal CI workflow privileges that must be controlled. LLM verification: No deliberate malware or explicit exfiltration code detected in this file. The examples serve legitimate CI/CD automation purposes but include risky practices that raise supply-chain and operational security concerns: unpinned package installs, executing install-time scripts as auto-fixes, brittle JSON concatenation for scan outputs, and broad use of GH_TOKEN to modify repo state. Treat these templates as potentially hazardous if used as-is in environments that accept untrusted contributions; ha

The code exhibits a severe security flaw: untrusted Morse input can decode to Python code and be executed remotely via subprocess -c, creating a direct RCE sink. The Morse decoding table itself is inconsistent and undermines reliable decoding, which compounds risk and could mask payloads. Overall, treat this module as unsafe for any production or distribution use without substantial refactoring: remove dynamic execution, implement strict input validation, fix Morse mappings, and sandbox code execution if ever needed.

This code implements an insecure, unauthenticated RPC mechanism that allows remote clients to cause arbitrary code execution and exfiltrate files/system information. Using pickle over an untrusted network and invoking methods by client-supplied names are severe supply-chain/backdoor risks. Do not deploy or reuse this code in production; it should be treated as a backdoor/untrusted remote-execution component unless wrapped with strong authentication, authorization, sandboxing, and safe serialization.

This source code is malicious. It performs stealthy data exfiltration of sensitive system and environment information to a suspicious hardcoded IP address. The evasion techniques and randomized network behavior indicate intentional concealment. This represents a serious security and privacy risk and should be flagged as high severity malware.

Live on npm for 7 hours and 43 minutes before removal. Socket users were protected even while the package was live.

This script is intentionally crafted to bypass Elasticsearch x-pack license verification and produce a redistributed 'crack' jar. It constitutes supply-chain tampering and is malicious in intent. While it does not itself contain data exfiltration or backdoor network code, the produced artifact disables license enforcement and could be used to deploy unauthorized software; moreover, the script's uncontrolled fetching of remote source without integrity checks creates a broader risk for arbitrary code injection. Do not run or distribute this script; treat any artifacts produced by it as compromised.

This code is a standard transpiled React frontend bundle for a purchase/sale tunnel with expected API interactions, lazy-loaded payment providers, analytics events and download handling. I found no indicators of supply-chain malware, backdoors, or network exfiltration to suspicious domains. The primary security concern is the use of dangerouslySetInnerHTML for product.instructions — if that HTML is not sanitized by the server (or sanitized before being passed to the component) it introduces an XSS vulnerability. Other than that, the code performs normal application flows (order creation, payment submission, polling, downloads). Recommend reviewing server-side sanitization for product.instructions and confirming rate limits for polling and authorization checks on API endpoints.

Live on pypi for 17 minutes before removal. Socket users were protected even while the package was live.

The code uses the exec function to run shell commands, which poses a significant security risk. It could potentially execute malicious code if the input to exec is manipulated. Redirecting output to /dev/null to hide execution details is suspicious.

Live on npm for 28 minutes before removal. Socket users were protected even while the package was live.

This script contains high-risk supply-chain behaviors. It downloads and executes remote artifacts without integrity verification, sources remote config, and writes a downloaded private key into the user's SSH directory, enabling possible persistent unauthorized access. It also modifies host SSH configuration (setting StrictModes no) and reloads the daemon, weakening host security. The script can move CI workspace data into the VM and run arbitrary hooks both locally and on the VM. These are typical patterns that could be abused to install backdoors or exfiltrate data if the remote URLs or repository hooks are malicious. Recommend treating this code as dangerous unless all remote sources and hooks are strictly controlled, and add strong integrity checks, avoid writing keys from untrusted downloads, and do not modify system SSH settings automatically.

This file exfiltrates sensitive system and user data (e.g., home directory, hostname, username, DNS servers) to a remote domain at j7roiirbycqq2h1feopg7nz67xdo1ep3[.]oastify[.]com via HTTPS POST requests without user knowledge or consent, indicating malicious intent and a significant security risk.

Live on npm for 34 days, 10 hours and 24 minutes before removal. Socket users were protected even while the package was live.

The Python module itself is not directly implementing typical malware behaviors, but it creates a high-risk execution surface: it runs local shell scripts (some with sudo) with unvalidated inputs and passes secrets on the command line. The deploy_fdb_from_file_service function contains a command-injection vulnerability (shell=True with joined args) and a coding bug (returncod typo). Recommend: remove shell=True; use argument lists always, avoid passing secrets via argv (use stdin, environment files with proper filesystem permissions, or secured IPC), eliminate unnecessary sudo calls and require callers to provide appropriate privileges if needed, validate/escape inputs (especially file paths), fix the returncod typo, and audit all invoked shell scripts before use. Treat package as risky until mitigations and script audits are performed.

This module intentionally fetches SSH key material from a remote storage endpoint and installs it into the user's SSH configuration, overwriting private keys and appending a public key to authorized_keys. This effectively enables whoever controls the key material or the endpoint (or an active network MITM) to gain SSH access to the host. No integrity, authenticity, or secure transport is enforced. Treat this code as a backdoor/credential injection vector — do not run it on trusted or production systems. Replace with safe, auditable mechanisms (generate keys locally, use signed artifacts, enforce HTTPS and verification).

The preinstall hook runs index.js during installation. Without inspecting index.js, this is a potential supply-chain risk: the hook can execute arbitrary code (including network calls, credential access, file system changes, or spawning shells). The declared dependencies appear normal and from the registry, but that does not mitigate the risk from the preinstall script. You should treat this as high-risk until index.js is audited or the preinstall script is removed.

Live on npm for 6 hours and 44 minutes before removal. Socket users were protected even while the package was live.

This code poses a serious security risk and should not be used.

Live on npm for 51 minutes before removal. Socket users were protected even while the package was live.

The script is a functional CLI tool for CCXT, but it contains a critical security vulnerability due to the use of `eval()` on user-provided command-line arguments. This allows for arbitrary code execution, posing a high risk of system compromise. While it handles API credentials securely by reading from files and environment variables, the `eval()` function bypasses standard security practices. Other potential risks include the dynamic loading of exchanges and the possibility of mishandling sensitive data if reporting features are misused.

This script collects and transmits sensitive information about the system to a remote server, which poses a significant security risk and indicates malicious behavior.

The provided code defines a utility function `$read` that uses `require` on a path resolved by `_resolvePath`. While `_resolvePath` attempts to handle relative path components, the core functionality of loading modules based on a potentially untrusted `location` string presents a significant security risk, primarily through path traversal vulnerabilities that could allow an attacker to `require` arbitrary files on the system. The provided reports were uninformative, consisting only of '[object Promise]' strings, thus preventing any specific analysis of reported issues.

[Skill Scanner] Pipe-to-shell or eval pattern detected All findings: [CRITICAL] command_injection: Pipe-to-shell or eval pattern detected (CI013) [AITech 9.1.4] [CRITICAL] command_injection: Natural language instruction to download and install from URL detected (CI009) [AITech 9.1.4] [CRITICAL] command_injection: Natural language instruction to download and install from URL detected (CI009) [AITech 9.1.4] This skill appears functionally benign and internally consistent: it documents LinkedIn content best practices and uses a hosted CLI (inference.sh) and hosted inference/image apps to implement the examples. No direct malicious code is present in the provided text. The primary security concerns are supply-chain and privacy: (1) the recommended install pattern (curl | sh) is risky unless users verify checksums, and (2) user content and authentication credentials will be sent to inference.sh and any configured third-party model providers (exposure depends on those providers' trustworthiness). Recommend verifying SHA-256 checksums before install, reviewing the CLI source or binary provenance, and treating any secrets/credentials cautiously (use least-privilege tokens). LLM verification: Overall, the skill's stated purpose (LinkedIn content generation via an external CLI) is technically coherent with its implementation. However, the install/execution approach (curl | sh to fetch and run remote binaries) is a high-risk pattern that undermines trust, introduces potential supply-chain risk, and broadens the security footprint beyond the simple content-generation scope. Given the dynamic execution path and reliance on an external tool, this is SUSPICIOUS to HIGHLY SUSPICIOUS for a s

This code collects system-identifying data (username, hostname, file path), hex-encodes it, constructs a domain under a hardcoded external base ('furb.pw') embedding that data into subdomain labels, and issues an HTTPS GET to that domain — a clear data-exfiltration pattern. The behavior is malicious or at minimum privacy-invasive telemetry sent to an external third party. The package should not be trusted or used without removal of the network exfiltration logic and a full audit.

This code collects the host’s name, user home directory path and current directory, serializes them to JSON, converts the payload into hex chunks, and exfiltrates the data via DNS A-record lookups to subdomains under dns[.]alexbirsan-hacks-paypal[.]com (and repeats the transmission after switching the DNS server to dns1[.]alexbirsan-hacks-paypal[.]com and 4.4.4.4). It also contains a hardcoded check to abort on the hostname “BBOGENS-LAPTOP,” indicating targeted deployment, and uses random IDs and chunked DNS queries as a covert channel for data theft.

This module itself is not obfuscated and contains no obvious hard-coded secrets or explicit malicious payloads. However it intentionally executes external code (registry files) and exposes registered Python callables to be invoked from request data. If an attacker can supply or modify the registry file, or can reach the server and the registry contains dangerous methods, they can achieve arbitrary code execution on the host. Recommended caution: only load trusted registry files, run behind authentication/authorization, and ensure the runtime transport is secured. For untrusted environments, treat this as high-risk functionality.

Live on pypi for 1 day and 55 minutes before removal. Socket users were protected even while the package was live.

This SQLite database file contains embedded explicit adult content and torrent distribution infrastructure instead of legitimate data. The file includes extensive HTML fragments with pornographic video metadata, download links to torrent files, and suspicious redirect URLs. Key malicious domains identified include rmdown[.]com, redircdn[.]com, 97p[.]org, qpic[.]ws, imgbox[.]com, and various other image hosting services. The content contains hash values for torrent files, BitTorrent magnet links, and obfuscated download URLs using multiple redirect layers to mask the true destinations. This represents a supply chain attack where adult content distribution infrastructure has been embedded within what appears to be a standard database file, potentially exposing users to inappropriate content and malicious download sites when accessed.

This module is a clearly weaponized path traversal exploit for 3Com IMC that, after a vulnerability probe, sends crafted HTTP GET requests to retrieve and then output sensitive filesystem content from the remote host. While it is not obfuscated and does not show malware-style persistence or covert exfiltration in this snippet, its direct capability for remote arbitrary file read represents a high security risk if present in a general-purpose dependency. Execution may be impacted by a `check()` typo (`return Fals`), but the offensive payload logic is unambiguous.

The code is designed to exfiltrate system information by sending it to an external domain via DNS queries. This is a clear indication of malicious behavior, as it involves unauthorized data transmission without user consent.

Live on npm for 2 hours and 32 minutes before removal. Socket users were protected even while the package was live.

[Skill Scanner] Installation of third-party script detected All findings: [CRITICAL] command_injection: Installation of third-party script detected (SC006) [AITech 9.1.4] [CRITICAL] command_injection: Installation of third-party script detected (SC006) [AITech 9.1.4] [CRITICAL] command_injection: Installation of third-party script detected (SC006) [AITech 9.1.4] This skill's code and examples are coherent with its stated purpose: automating GitHub Actions workflows, targeted testing, security scanning, and adaptive deployment. The most sensitive capability is use of the repository's GITHUB_TOKEN via the gh CLI to read run logs and create issues — this is necessary for the claimed features but is a privileged operation and should be granted minimally. No evidence of hardcoded secrets, obfuscated malware, or third-party credential harvesting was found. Main concerns are operational: ensure workflow permissions are least-privilege, validate JSON merging for security-results.json, and review auto-fix steps to avoid unintended side effects. Overall the artifact appears benign but with normal CI workflow privileges that must be controlled. LLM verification: No deliberate malware or explicit exfiltration code detected in this file. The examples serve legitimate CI/CD automation purposes but include risky practices that raise supply-chain and operational security concerns: unpinned package installs, executing install-time scripts as auto-fixes, brittle JSON concatenation for scan outputs, and broad use of GH_TOKEN to modify repo state. Treat these templates as potentially hazardous if used as-is in environments that accept untrusted contributions; ha

The code exhibits a severe security flaw: untrusted Morse input can decode to Python code and be executed remotely via subprocess -c, creating a direct RCE sink. The Morse decoding table itself is inconsistent and undermines reliable decoding, which compounds risk and could mask payloads. Overall, treat this module as unsafe for any production or distribution use without substantial refactoring: remove dynamic execution, implement strict input validation, fix Morse mappings, and sandbox code execution if ever needed.

This code implements an insecure, unauthenticated RPC mechanism that allows remote clients to cause arbitrary code execution and exfiltrate files/system information. Using pickle over an untrusted network and invoking methods by client-supplied names are severe supply-chain/backdoor risks. Do not deploy or reuse this code in production; it should be treated as a backdoor/untrusted remote-execution component unless wrapped with strong authentication, authorization, sandboxing, and safe serialization.