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HistoryMay 02, 2022 - 3:40 a.m.

PyGreSQL Might Be Vulnerable to Encoding-Based SQL Injection

2022-05-0203:40:08
Google
osv.dev
2

7.8 High

AI Score

Confidence

Low

7.5 High

CVSS2

Access Vector

NETWORK

Access Complexity

LOW

Authentication

NONE

Confidentiality Impact

PARTIAL

Integrity Impact

PARTIAL

Availability Impact

PARTIAL

AV:N/AC:L/Au:N/C:P/I:P/A:P

0.011 Low

EPSS

Percentile

83.9%

PyGreSQL 3.8 did not use PostgreSQL’s safe string and bytea functions in its own escaping functions. As a result, applications written to use PyGreSQL’s escaping functions are vulnerable to SQL injections when processing certain multi-byte character sequences. Because the safe functions require a database connection, to maintain backwards compatibility, pg.escape_string() and pg.escape_bytea() are still available, but applications will have to be adjusted to use the new pyobj.escape_string() and pyobj.escape_bytea() functions. For example, code containing:

import pg
connection = pg.connect(...)
escaped = pg.escape_string(untrusted_input)

should be adjusted to use:

import pg
connection = pg.connect(...)
escaped = connection.escape_string(untrusted_input)
CPENameOperatorVersion
pygresqleq4.0
pygresqleq3.8.1

7.8 High

AI Score

Confidence

Low

7.5 High

CVSS2

Access Vector

NETWORK

Access Complexity

LOW

Authentication

NONE

Confidentiality Impact

PARTIAL

Integrity Impact

PARTIAL

Availability Impact

PARTIAL

AV:N/AC:L/Au:N/C:P/I:P/A:P

0.011 Low

EPSS

Percentile

83.9%