Friday, December 7, 2018

Kubernetes Privilege Escalation (CVE-2018-1002105)

Introduction

Kubernetes is an open source production grade container orchestration system for deploying and managing docker/container applications. There are managed kubernetes orchestration service providers like Amazon Elastic Container Service for Kubernetes (EKS), Azure Kubernetes Service (AKS) etc.

kubectl

Kubernetes cluster users can perform management tasks using kubectl binary which talks to API Server. Example kubectl commands

# display pod resource
kubectl get pods -n my_namespace

# Execute a command in a container
kubectl -n my_namespace exec -it pods_name -- sh


# Listen on ports 5000 and 6000 locally, forwarding data to/from ports 5000 and 6000 in the pod
kubectl -n my_namespace port-forward pod/mypod 5000 6000

# Get output from ruby-container from pod my-pod-pd

kubectl attach my-pod-pd -c ruby-container


kubectl execution flow (source: 1ambda.github.io)


kubelet

kubelet, kube-proxy run's on each compute node (VM, Worker, EC2 Instance etc), kubelet listens on TCP port 10250 and 10255 (with no authentication/authorization). API Server acts as Reverse Proxy to kubelet and API Aggregation. API Server connects to the kubelet to fulfill commands like exec, port=forward and opens a websocket connection which connects stdin, stdout, or stderr to user’s original call [01].

API Aggregation

Installing or writing additional API's into Kubernetes API Server i.e. extending core API Server

Vulnerability

Vulnerability is in Kubernetes API Server, crafted request can execute arbitrary commands on the backend servers (pods) through the same channel client established to backend through API Server [02]

Check nodes Kubernetes version
$ kubectl get nodes -o wide
NAME        STATUS ROLES AGE VERSION INTERNAL-IP EXTERNAL-IP OS-IMAGE KERNEL-VERSION CONTAINER-RUNTIME
pd-worker-01 Ready node 13d v1.12.3 10.250.0.6 Container Linux by CoreOS 1745.7.0 (Rhyolite) 4.14.48-coreos-r2 docker://18.3.1
pd-worker-02 Ready node 13d v1.12.3 10.250.0.5 Container Linux by CoreOS 1745.7.0 (Rhyolite) 4.14.48-coreos-r2 docker://18.3.1
pd-worker-03 Ready node 13d v1.12.3 10.250.0.4 Container Linux by CoreOS 1745.7.0 (Rhyolite) 4.14.48-coreos-r2 docker://18.3.1


Vulnerable API Servers

If API server response looks as bellow and using vulnerable API versions of Kubernetes the you are vulnerable using anonymous-user escalation, patch Kubernetes immediately.
HTTP response error code 403 indicates Forbidden i.e. related to Authorization implies we successfully passed through Authentication phase.
{ "kind": "Status", "apiVersion": "v1", "metadata": { }, "status": "Failure", "message": "forbidden: User \"system:anonymous\" cannot get path \"/api/v1/\"", "reason": "Forbidden", "details": { }, "code": 403 }


anonymous user

By default, requests to the kubelet’s HTTPS endpoint that are not rejected by other configured authentication methods are treated as anonymous requests, and given a username of system:anonymous and a group of system:unauthenticated.

Mitigations

There are three levels of escalation mitigations

1. anonymous user -> aggregated API server

API Server admission-controller parameter anonymous-auth is set to fault
$ kubectl get po kube-apiserver-01 -n prod -o yaml | grep -i "anonymous-auth" - --anonymous-auth=false 
$ kubectl get po kube-apiserver-01 -n stage -o yaml | grep -i "anonymous-auth" - --anonymous-auth=false


2. authenticated user -> aggregated API server

Suspend aggregated API servers usage


3. authorized pod exec/attach/portforward -> kubelet API

Remove pod exec/attach/portforward permissions for users


References

[01]. https://docs.openshift.com/container-platform/3.11/architecture/networking/remote_commands.html
[02]. https://docs.openshift.com/container-platform/3.11/architecture/networking/remote_commands.html
[03]. https://elastisys.com/2018/12/04/kubernetes-critical-security-flaw-cve-2018-1002105/
[04]. https://github.com/kubernetes/kubernetes/issues/71411



Saturday, January 20, 2018

AWS VPC Flow Logs grok Pattern


Amazon Web Services(AWS) can generate VPC flow logs, format below
2 123456789010 eni-abc123de 172.31.9.69 172.31.9.12 49761 3389 6 20 4249 1418530010 1418530070 REJECT OK

For more information on flow logs and grok filter plugin refer below links
https://docs.aws.amazon.com/AmazonVPC/latest/UserGuide/flow-logs.html
https://www.elastic.co/guide/en/logstash/current/plugins-filters-grok.html

grok patterns can be tested using below links
http://grokdebug.herokuapp.com
http://grokconstructor.appspot.com/do/match#result

%{NONNEGINT:version} %{NONNEGINT:accountid} %{NOTSPACE:interface-id} %{NOTSPACE:srcaddr} %{NOTSPACE:dstaddr} %{NONNEGINT:srcport} %{NONNEGINT:dstport} %{NONNEGINT:protocol} %{NONNEGINT:packets} %{NONNEGINT:bytes} %{NONNEGINT:starttime} %{NONNEGINT:endtime} %{NOTSPACE:action} %{NOTSPACE:log-status}

Test using grokdebugger

Test using grokconstructor

You can also consider INT instead of NONNEGINT


Found few patterns by googling which looked like below, were not working on grokconstructor website.
%{NUMBER:version} %{NUMBER:account-id} %{NOTSPACE:interface-id} %{NOTSPACE:srcaddr} %{NOTSPACE:dstaddr} %{NOTSPACE:srcport:int} %{NOTSPACE:dstport:int} %{NOTSPACE:protocol:int} %{NOTSPACE:packets:int} %{NOTSPACE:bytes:int} %{NUMBER:start:int} %{NUMBER:end:int} %{NOTSPACE:action} %{NOTSPACE:log-status}

Tested on grokdebugger


Tested on grokconstructor

We can use the extracted variables from grok filter plugin in Kibana search or enhance data using logstash filter plugins geoip, dns, date etc.

Working in or using Python virtualenv

Install Python virtualenv on Ubuntu using below command
apt-get -y install python-virtualenv

Create virtualenv
$virtualenv test_env1
New python executable in test_env1/bin/python

$. test_env1/bin/activate
Or
$source test_env1/bin/activate

Exit virtualenv
$deactivate

Switch between virtualenv’s
$workon test_env2

List all available virtualenv’s
$workon


virtualenvwrapper comes with few handy commands

$pip install virtualenvwrapper

virtualenvwrapper supports extra commands like
mkvirtualenv
cdvirtualenv
rmvirtualenv

Saturday, December 23, 2017

Linux: Recovering files deleted using "rm -rf"


Removed python script file by accident. Following two methods worked for me in retrieving the file.

Trick 1:
This was posted on askubuntu.com

$grep -a -B 40 -A 80 'string_from_file' /dev/sda1 > save_here.txt

-A 100 save 80 lines after match
-B 40 save 40 lines before match
string_from_file at least one unique string you remembered from deleted file
save_here.txt    retrieved content is copied here

Trick 2:
$lsof | grep -i "/path/to/file"
progname 1234 user_name 44 8,1 43219876 432890 /path/to/file
$cp /proc/1234/fd/44 /restore/file/tothis/path

Retrieved files might have unnecessary data or few lines might be arranged in reverse order.



Tuesday, October 17, 2017

FinTech, Mobile Applications and Vulnerabilities




MOBILE APPLICATION VULNERABILITIES
Reverse Engineering: Applications published on Google Play or Apple App Store can be reverse engineered by malicious users and create similar applications. Companies can lose their intellectual property.
Insecure Data Storage: FinTech related applications save sensitive data like personally identifiable information (PII), card data (PCI), health information etc. Sensitive personal information saved on mobile should be encrypted.
SSL Pinning bypass: SSL Pinning will
One Time Password: OTP is used as second level of authentication.
OTP Spamming: OTP Spamming is requesting an API/URL which generates OTP by spoofing mobile number to victims phone number. If there is no proper validation, attacker can send many OTP SMS’s to victim phone
OTP Bypass:
-       Modifying checks: OTP validation can be bypassed by modifying checks in the request payload or URI parameters
-       Bypassing SS7
-       Malicious mobile apps sniffing OTP’s

WEB APPLICATION VULNERABILITIES
All OWASP Top 10 or SANS Top 25 Vulnerabilities will be applicable.
- Cross Site Scripting (XSS): If the input values from user is not validated it might lead to java script execution vulnerabilities which might lead to cookie theft, redirection to malicious websites, DDoS attacks on other sites etc..
- SQL Injection: Improper input validation might lead to SQL Injection.
Privilege Escalation: If the authorization is not enforced properly, one user can access other users data.
- Authentication bypass
            SQL Injection
            Session ID Guessing
            Cookie values
- Command Execution: Improper input validation might lead to OS command execution
- Serialization/Deserialization: Data interpreted as code because of improper validation. This might lead to code execution in Java, PHP, Python
- CSRF
- WAF Bypass
- Ratelimiting Issues
            Important API’s
            Forgot/Reset Password
            Login page
            Other important/sensitive API’s
- XXE (XML External Entity) Attack
- SSRF (Server Side Request Forgery)
- JSON Injection
- DoS/DDoS (Layer 3, Layer 4 and Layer 7 attacks)

AWS INFRA
- Public S3 buckets: Will have files
- Public EBS Volumes: Might have sensitive information like SSH Keys, Server Keys, passwords etc.
- No Multi Factor Authentication (MFA, 2FA) to AWS
- Root logins
- Token Disclosure
            Slack
            Git

MISCELLANEOUS       
Crypto Currency based exploitation in future
Sub-domain takeover
Vulnerabilities in protocols

-->
Vulnerabilities in Hardware

Saturday, April 8, 2017

Vault7: Malware and Disk I/O (Input Output)

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Following were the guidelines given to Malware authors at CIA, how to deal with Disk I/O and steps taken to save data on to disk or deleting saved date from disk.
DirectiveRationale
DO explicitly document the "disk forensic footprint" that could be potentially created by various features of a binary/tool on a remote target.
Enables better operational risk assessments with knowledge of potential file system forensic artefacts.
DO NOT read, write and/or cache data to disk unnecessarily. Be cognizant of 3rd party code that may implicitly write/cache data to disk.Lowers potential for forensic artefacts and potential signatures.
DO NOT write plain-text collection data to disk.Raises difficulty of incident response and forensic analysis.
DO encrypt all data written to disk.Disguises intent of file (collection, sensitive code, etc) and raises difficulty of forensic analysis and incident response.
DO utilize a secure erase when removing a file from disk that wipes at a minimum the file's filename, datetime stamps (create, modify and access) and its content.
(Note: The definition of "secure erase" varies from filesystem to filesystem, but at least a single pass of zeros of the data should be performed. The emphasis here is on removing all filesystem artefacts that could be useful during forensic analysis)
Raises difficulty of incident response and forensic analysis.
DO NOT perform Disk I/O operations that will cause the system to become unresponsive to the user or alerting to a System Administrator.
Avoids unwanted attention from the user or system administrator to tool's existence and behavior.
DO NOT use a "magic header/footer" for encrypted files written to disk. All encrypted files should be completely opaque data files.Avoids signature of custom file format's magic values.
DO NOT use hard-coded filenames or filepaths when writing files to disk. This must be configurable at deployment time by the operator.Allows operator to choose the proper filename that fits with in the operational target.
DO have a configurable maximum size limit and/or output file count for writing encrypted output files.
Avoids situations where a collection task can get out of control and fills the target's disk; which will draw unwanted attention to the tool and/or the operation.