ml-core-airflow-authPyPI
ml-core-airflow-auth is a confirmed malicious PyPI package (MAL-2026-10919) that steals credentials and exfiltrates sensitive data (malicious version 0.0.1). Do not install it — remove it immediately and rotate any exposed credentials.
Malicious code in ml-core-airflow-auth (PyPI)
What this malware does
The package advertises itself as an 'auth token handler' but its public API (src/ml_core_airflow_auth/init.py) exposes only a trivial in-memory TokenStore stub unrelated to the ~3300 LOC of hidden telemetry code shipped alongside. The setup.py custom install command copies telemetry.pth into site-packages; that.pth file contains import _telemetry_init, causing every subsequent Python interpreter start on the host to auto-load _telemetry_init._bootstrap, which spawns a daemon thread that constructs an analytics Client (Envelope, HttpTransport, ServiceDiscovery, DataScrubber, SessionTracker) and calls client.track('session_start') with the machine's hostname, OS, Python version, and cpu_count. The reporting endpoint is not a static URL; _telemetry_transport.py's ServiceDiscovery opens a raw UDP DNS socket with hardcoded fallback resolvers 8.8.8.8 and 1.1.1.1, queries TXT records under 0.<domain>... N.<domain>, and reconstructs the destination via base64.b64decode(''.join(segments)), letting the operator change the exfiltration destination post-install without republishing. The name, generic 'Platform Engineering' author, and mismatch between the declared purpose and the hidden persistent telemetry framework are consistent with dependency-confusion targeting corporate ML/Airflow environments.
Package presents little functionality, but excessive fake 'telemetry' module. This fake telemetry is used to download and run malicious executables. Code is designed to survive different blocks: first, there is an attempt to download the executable from one of five Cloudflare Workers. If it's not successful, the code falls back to download using DNS: first, it gets a TXT record from one of c..dl.well1[.]site domains, depending on the system. This record returns a number, which is then used to iterate over domains in the form <0...n>..dl.well1[.]site and reconstruct the encoded executable from their TXT records. The downloaded binary is then executed and removed afterward. Using a PTH file ensures persistence and runs on every Python start. In this campaign, versions 0.0.1 hold disarmed code (without the necessary configuration), which is completed in further updates.
This is a continuation of the 2026-07-haproxy-config-client campaign.
Category: MALICIOUS - The campaign has clearly malicious intent, like infostealers.
Campaign: 2026-07-andreiiiiiii_i
Reasons (based on the campaign):
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The package contains code to exfiltrate basic data from the system, like IP or username. It has a limited risk.
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The package overrides the install command in setup.py to execute malicious code during installation.
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Downloads and executes a remote executable.
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covering-tracks
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persistence
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abuses-pth
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data-stored-in-dns
Malicious versions
Indicators of compromise (SHA-256)
Detection & response playbook
Credential / info stealerFind it
Scan your lockfiles (package-lock.json, pnpm-lock.yaml, yarn.lock, requirements.txt, poetry.lock, etc.) and build artifacts for ml-core-airflow-auth (version 0.0.1). O3 Security's supply-chain scanner checks every dependency against known-malicious package intelligence at install time and in CI, flagging ml-core-airflow-auth across your stack and pipelines.
If you installed it — respond
ml-core-airflow-auth is built to steal secrets, so assume every credential the build or runtime could read is compromised. Remove it from your project and lockfile, then rotate ALL exposed secrets — npm/registry tokens, cloud keys, CI/CD secrets, SSH keys, and any .env values — from a known-clean machine. Audit logs for unauthorized use of those credentials.
Did it already run?
If ml-core-airflow-auth was ever installed, its post-install/runtime payload may have already executed. O3's L7 egress monitoring and runtime eBPF sensors detect the credential exfiltration or command-and-control callback after install and block the malicious outbound channel, so you catch and contain the actual compromise — not just the presence of the package.
How O3 protects you
O3 blocks ml-core-airflow-auth before install through its supply-chain scanner, and if it has already run, detects and severs the exfiltration or C2 callback at runtime through L7 egress monitoring and eBPF.
Frequently asked questions
Campaign
References
Credits
- Amazon Inspector · finder
- Kamil Mańkowski (kam193) · reporter
Detect & block this
O3 blocks ml-core-airflow-auth-class packages before install and in CI — and if it already ran, its runtime egress monitoring catches the credential exfiltration and severs the channel.