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Keywords {🔍}

security, dos, large, issue, fixes, cve, prevent, gpshead, conversions, int, add, doc, missing, places, python, sign, eol, end, life, code, pull, requests, projects, intstr, integer, string, navigation, cpython, actions, cpu, time, base, decimal, data, input, length, values, response, team, limit, added, typebug, unexpected, behavior, bug, error, typesecurity, mentioned, typefeature, feature,

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security issue projects security fixes type-bug python steering council enhancement type-security error type-feature linear-time conversions linear time conversions loading large values personal information cve-2020-10735 efficient algorithm exists user controlled inputs… add doc missing bedevere-bot mentioned adding length guards existing code projects milestone cpu consuming dos linked prs gh-95778 large int security fixes 3 string conversions feature request large number cpu time int implementation cpython prevent dos binary bignum quadratic amount data serialization input length similar concept hexadecimal stored untrusted data vast majority weeks ago unexpected behavior milestone relationships issue github huge integer cve-2020-10735 int bug dos input string integer 11] gh-95778 gh-100627

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      headline:CVE-2020-10735: Prevent DoS by large int<->str conversions
      articleBody:## Problem A Denial Of Service (DoS) issue was identified in CPython because we use binary bignum’s for our `int` implementation. A huge integer will always consume a near-quadratic amount of CPU time in conversion to or from a base 10 (decimal) string with a large number of digits. No efficient algorithm exists to do otherwise. It is quite common for Python code implementing network protocols and data serialization to do `int(untrusted_string_or_bytes_value)` on input to get a numeric value, without having limited the input length or to do `log("processing thing id %s", unknowingly_huge_integer)` or any similar concept to convert an `int` to a string without first checking its magnitude. (`http`, `json`, `xmlrpc`, `logging`, loading large values into integer via linear-time conversions such as hexadecimal stored in `yaml`, or anything computing larger values based on user controlled inputs… which then wind up attempting to output as decimal later on). All of these can suffer a CPU consuming DoS in the face of untrusted data. Everyone auditing all existing code for this, adding length guards, and maintaining that practice everywhere is not feasible nor is it what we deem the vast majority of our users want to do. This issue has been reported to the Python Security Response Team multiple times by a few different people since early 2020, most recently a few weeks ago while I was in the middle of polishing up the PR so it’d be ready before 3.11.0rc2. ## Mitigation After discussion on the Python Security Response Team mailing list the conclusion was that we needed to limit the size of integer to string conversions for non-linear time conversions (anything not a power-of-2 base) by default. And offer the ability to configure or disable this limit. The Python Steering Council is aware of this change and accepts it as necessary. <!-- gh-linked-prs --> ### Linked PRs * gh-100627 * gh-100628 * gh-101065 * gh-101066 * gh-101630 * gh-101631 <!-- /gh-linked-prs -->
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      headline:CVE-2020-10735: Prevent DoS by large int<->str conversions
      articleBody:## Problem A Denial Of Service (DoS) issue was identified in CPython because we use binary bignum’s for our `int` implementation. A huge integer will always consume a near-quadratic amount of CPU time in conversion to or from a base 10 (decimal) string with a large number of digits. No efficient algorithm exists to do otherwise. It is quite common for Python code implementing network protocols and data serialization to do `int(untrusted_string_or_bytes_value)` on input to get a numeric value, without having limited the input length or to do `log("processing thing id %s", unknowingly_huge_integer)` or any similar concept to convert an `int` to a string without first checking its magnitude. (`http`, `json`, `xmlrpc`, `logging`, loading large values into integer via linear-time conversions such as hexadecimal stored in `yaml`, or anything computing larger values based on user controlled inputs… which then wind up attempting to output as decimal later on). All of these can suffer a CPU consuming DoS in the face of untrusted data. Everyone auditing all existing code for this, adding length guards, and maintaining that practice everywhere is not feasible nor is it what we deem the vast majority of our users want to do. This issue has been reported to the Python Security Response Team multiple times by a few different people since early 2020, most recently a few weeks ago while I was in the middle of polishing up the PR so it’d be ready before 3.11.0rc2. ## Mitigation After discussion on the Python Security Response Team mailing list the conclusion was that we needed to limit the size of integer to string conversions for non-linear time conversions (anything not a power-of-2 base) by default. And offer the ability to configure or disable this limit. The Python Steering Council is aware of this change and accepts it as necessary. <!-- gh-linked-prs --> ### Linked PRs * gh-100627 * gh-100628 * gh-101065 * gh-101066 * gh-101630 * gh-101631 <!-- /gh-linked-prs -->
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