CVE-2026-45036 (GCVE-0-2026-45036)
Vulnerability from cvelistv5 – Published: 2026-05-15 16:47 – Updated: 2026-05-20 15:42
VLAI
EPSS
VEX
Title
Tabby auto-confirms ZMODEM detection on terminal output, leading to shell command execution from displayed file content under fish, bash, and zsh
Summary
Tabby (formerly Terminus) is a highly configurable terminal emulator. Prior to 1.0.233, Tabby before 1.0.233 automatically confirms ZMODEM protocol detection on all terminal session output without user interaction, enabling shell command execution when a user displays attacker-controlled content. The ZModemMiddleware in tabby-terminal consumes all session output through a Zmodem.Sentry, and when a ZMODEM ZRQINIT header is detected, unconditionally calls detection.confirm() and writes a fixed ZRINIT response ( **\x18B0100000023be50\r\n\x11) back into the active PTY as input. When the process that triggered the detection (e.g., cat) exits, the injected bytes are consumed by the user's shell as a command line. Under fish (default configuration), the ** prefix triggers recursive glob expansion against the current directory, allowing an attacker-placed executable at a matching nested path (e.g., d/xB0100000023be50) to be executed by relative pathname without relying on PATH. Under bash and zsh, a secondary xterm.js terminal color-query feedback (OSC 10) can be combined in the same file to inject a slash-containing command word that similarly bypasses PATH resolution. An attacker can exploit this by providing a crafted file (e.g., in a cloned Git repository) that a user displays with cat, achieving code execution with no interaction beyond viewing the file. This vulnerability is fixed in 1.0.233.
Severity
SSVC
Exploitation: none
Automatable: no
Technical Impact: total
CISA Coordinator · CISA-ADP (v2.0.3)
Decision recorded 2026-05-20 03:55 UTC
CWE
- CWE-78 - Improper Neutralization of Special Elements used in an OS Command ('OS Command Injection')
Assigner
References
1 reference
| URL | Tags |
|---|---|
| https://github.com/Eugeny/tabby/security/advisori… | x_refsource_CONFIRM |
Impacted products
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Experimental. This forecast is provided for visualization only and may change without notice. Do not use it for operational decisions.
Forecast uses a logistic model when the trend is rising, or an exponential decay model when the trend is falling. Fitted via linearized least squares.
Sightings
| Author | Source | Type | Date | Other |
|---|
Nomenclature
- Seen: The vulnerability was mentioned, discussed, or observed by the user.
- Confirmed: The vulnerability has been validated from an analyst's perspective.
- Published Proof of Concept: A public proof of concept is available for this vulnerability.
- Exploited: The vulnerability was observed as exploited by the user who reported the sighting.
- Patched: The vulnerability was observed as successfully patched by the user who reported the sighting.
- Not exploited: The vulnerability was not observed as exploited by the user who reported the sighting.
- Not confirmed: The user expressed doubt about the validity of the vulnerability.
- Not patched: The vulnerability was not observed as successfully patched by the user who reported the sighting.
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The MITRE ATT&CK techniques below are AI-generated suggestions, inferred from the description of the
vulnerability by the CIRCL/vulnerability-attack-technique-classification-roberta-base
model, served locally by ML-Gateway.
They have not been verified by an analyst and are provided for guidance only.
The approach is described in our paper Mapping CVEs to MITRE ATT&CK Techniques: A Curated Gold-Set Classifier and the Limits of LLM-Assisted Label Expansion.
Browse all ATT&CK techniques and the vulnerabilities related to each.
The approach is described in our paper Mapping CVEs to MITRE ATT&CK Techniques: A Curated Gold-Set Classifier and the Limits of LLM-Assisted Label Expansion.
Browse all ATT&CK techniques and the vulnerabilities related to each.
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Related by attack behaviour
Vulnerabilities whose description is nearest to this one in the vector space of the CIRCL/vulnerability-attack-technique-biencoder model. This is a similarity search over the bi-encoder space (plain cosine), not a classification, and it has no measured accuracy.
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