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Low 34 Bitcoin

fix(python): improve session handling and unlocking

Public commit record

What the developer wrote

Authored by matejcik

97/100 · Strong
fix(python): improve session handling and unlocking

* for trezorctl, implement custom version of `ensure_unlocked()` on
TrezorConnection, so that we can reuse the standard session which
unlocked the device
* move some of the passphrase handling into TrezorConnection in order
to avoid get_default_session, which has to call its own
ensure_unlocked()
* clean up features handling in client.get_session(), to properly handle
the case that features are locked

[no changelog]
✓ Specific, descriptive subject✓ Names a concrete action or component✓ Uses a recognizable type or scope✓ Provides detailed explanatory context✓ Explains rationale or failure mode
The short version

What changed, and why it matters

This commit refactors how the Trezor Python command-line tool (trezorctl) manages device sessions and unlocking. It aims to avoid creating duplicate sessions when unlocking the device and to handle passphrases more cleanly. The changes are framed by the developer as an improvement/fix to session handling, not as a response to a known security vulnerability. There is no public evidence that this fixes an exploitable bug.

Recommended action

Treat as a routine maintenance/refactor patch. Reviewers may want to verify that reusing the standard session does not leak passphrase-protected state between operations and that the cached features are invalidated appropriately on device state changes. No urgent security action is indicated by the commit alone.

Security signals we found

01

Refactor of device unlock/session reuse logic in CLI client

02

Removal of get_default_session() path that could trigger redundant ensure_unlocked() calls

03

Caching of standard session and features to avoid repeated state queries

04

Change from explicit `is True` to truthiness checks for feature flags

05

No changelog entry and no CVE/advisory references in commit

Risk score

Why this scored 34/100

Our methodology →
Potential impact 8/30
Exploitability 6/25
Stealth signal 5/15
Affected reach 7/15
Confidence 5/10
Evidence quality 3/5
Human-validated context

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