jmp anova

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Delphi Reverse Engineering Study Notes [2]

h0000: 00404DD4 lParam = word ptr 14 h// Four parameters and two local variables0000: 00404DD40000: 00404DD4 push ebp0000: 00404DD5 mov ebp, esp// Standard Delphi call framework0000: 00404DD7 add esp, 0FFFFFFB8h// Sub esp, 48 h. Note that the above Paint = PAINTSTRUCT ptr-48 h// It is quite interesting.0000: 00404DDA push ebx0000: 00404DDB xor ebx, ebx0000: 00404DDD mov eax, [ebp + Msg]0000: 00404DE0 cmp eax, 111 h; WM_COMMAND0000: 00404DE5 jg short loc_404E0B0000: 00404DE7 jz loc_404EF8// I ha

ESP interpretation in the Assembly

assigned to EBP, the value of the EBP register used to save the ESP value in this "Top program" will never change. Although it may change temporarily after entering the sub-call (used for the stack balance of the sub-call), after exiting, the original EBP value will be restored according to * Pop EBP.Taking this sentence as a breakthrough means that as long as we can break through the "top-Layer Program", we can observe the ESP value of EBP when the shell is between

Assembly tip 1

Assembly tip 1 Tip 1: Get the current instruction address and add the instruction {_ ASM{CallGet_next_addr; get the next JMP eax address and save it in eax.JMPEax; local jump, endless loop, waiting for correction to 0x90, 0x90 NOPMoVEax, 0x1JMPQuit _ Emit0x12; useless data flower command_ Emit0x34_ Emit0xff_ Emit0x4f_ Emit0xd3_ Emit0xe3_ Emit0x67_ Emit0x12_ Emit0x89_ Emit0x00 Get_next_addr:PopEaxPushEaxRETQuit:JMP gothis;}}Gothis:Printf ("Hello world!

Fully analyzes the jump rules between privileged-level and privileged-level code segments in chapter 3 of "writing an operating system by yourself"

types of transfer can be achieved using JMP or call commands: (1) The target operand contains the segment Selection Sub of the target code segment. (2) The target operand points to a call gate descriptor that contains the child selected by the target code segment. (3) The target operand points to a TSS that contains the child of the target code segment. (4) The target operand points to a task door, which points to a TSS containing the child of the ta

View the process of debugging from the MS03-049 vulnerability exploitation (figure)

. Fortunately, the ShellCode in this area has been written before, so it is ready for use. Now the rest is to find the overflow point and then modify it. For convenience, the following work is for Windows2000, and the current system partition is Fat32.Determine overflow points   The overflow is of course found from the ready-made code. Open the source code of the DOS window again and find two points worth attention, one of which is shown in Area 3: Javascript: if (this. width> 500) this. width =

The most detailed explanation I have ever seen is that the ESP law is shelled (recommended)

subroutine from JMP to call. For example:   00401029. E8 da240a00 call 004a3508   0040102e. 5A pop edX   After 00401029 is executed, the program will press 0040102e into the stack, and then JMP to 004a3508 address!   2. Ret   The corresponding call is ret. We can understand RET as follows: 1. Stack the address pointed to in the current ESP; 2. Send JMP to this a

Multi-thread inline API hook for Functions

There are many inline API hook methods. A common method does not require Embedded Assembly statements. The principle is simple and easy to understand, the 64-bit Microsoft operating system does not allow the embedded compilation of such unsolvable things to be awesome (the message provided by the great god of Lenin, I did not try it myself ). The principle of this method is briefly described below. First, let's talk about the principle of inline hook. There are a lot of details. I just want to m

Simple acquisition of Shellcode

realease,+16 debug *peip = (DWORD) UC; // RETN address point to ShellCode FUNC1 (CH);ShellCode Overflow 2Hmodule hmod = LoadLibrary ("user32.dll"); unsignedCharUc[] ="1234567890123456\x53\x93\xd2\x77\x33\xc0\x50\xc6\x04\x24\x6c\xc6\x44\x24\x01\x6c\x68\x72\x74\x2e" "\x64\x68\x6d\x73\x76\x63\x8b\xc4\x50\xb8\x7b\x1d\x80\x7c\xff\xd0" "\x33\xc0\x50\x68\x2e\x65\x78\x65\x68\x63\x61\x6c\x63\x8b\xc4\x50" "\xb8\xc7\x93\xbf\x77\xff\xd0\x33\xc0\x50\xb8\x7e\x9e\xc0\x77\xff"

GRUB SOURCE Analysis---1

Grub_boot_machine_drive_check macro is defined as 0x66, so it means that the next instruction from 0x7c00 to JMP 3f is altogether 102 bytes.JMP 3f has a total of two bytes and may be overwritten with two NOP instructions when GRUB is installed in the first sector, so check this below.The DL registers are set by the BIOS as the boot device number, typically the 0x80~0xff,0x80 number corresponding to the first hard drive. If the

Simple Goldbach conjecture of compilation

appears in both A and B in the array C1. Here's the full-text code DATAS SEGMENT num DW 0 y DW Ten flag DW 0 a DW 0 B DW 2 d DW 1 e DW 0 F DW 0 Both DW 2 flag2 DW 0 H1 DB "Please input a number:", ' $ ' H2 db 0AH,0DH, "Your input is inlow!", ' $ ' H3 DB 0AH,0DH, "the input must be even or greater than 6", ' $ ' DATAS ENDS STACKS SEGMENT DW-dup (0) STACKS ENDS CODES SEGMENT assume Cs:codes,ds:datas,ss:stacks main proc far push DS mov ax,0 push ax mov ax,datas mov Ds,ax Call input Call Chec

Simple linear regression implemented using PHP _ PHP

, naming schemes that are highly abbreviated are common in mathematical programming, but they make it more difficult to understand and prove whether a mathematical routine is step-by-step. Perfection is not a goal The goal of this coding exercise is not to develop a highly optimized and rigorous mathematical engine for PHP. In the early stages, we should emphasize the importance of analyzing and testing the implementation of learning and solve this problem. Instance variables When modeling a

R language Combat (eight) generalized linear model

(), Coef () Lists the parameters (intercept items and slopes) of the fitted model Confint () Give the confidence interval of the model parameter (default is 95%) Residuals () Lists the residuals value of the fitted model Anova () Variance analysis table for two fitted models Plot () Generate a diagnostic diagram of the evaluation F

ch8-Annual sales forecast for a car and enterprise-regression

nonlinear model estimation parameters is similar to the linear model, even if the residual squared and =min parameters are estimated, just at this time the model regression line is the curve.To build a segmented regression model:Attention:Regression results: The standard error of parameter estimation is approximate standard error, so the corresponding confidence interval is for reference only, and all output results do not give the test result of the parameter.In the results of

Simple linear regression implemented using PHP: (1)

rigorous mathematical engine for PHP. In the early stages, we should emphasize the importance of analyzing and testing the implementation of learning and solve this problem. Instance variables When modeling a statistical test or process, you need to specify which instance variables are declared. The selection of instance variables can be determined by the intermediate value and the total value generated by the analysis process. Each median value and aggregate value can have a corresponding i

ZZ collects kernel functions-kernel function

, the exponential would behave almost linearly and the higher-dimensional projection would start to lose its Non-linear power. In the other hand, if underestimated, the function would lack regularization and the decision boundary would be highly sensi tive to noise in training data.4. Exponential KernelThe exponential kernel is closely related to the Gaussian kernel and with the square of the norm left out. It is also a radial basis function kernel.5. Laplacian KernelThe Laplace Kernel is comple

[Statistics in small eyes] difference test and general linear model (1)

With the use of SPSS children's shoes are known, we commonly used variance analysis (ANOVA) in the general linear model (generic Linear models, called GLM) under the menu. And who is that GLM? Let's open the Magnum wiki and type the general Linear Model ... What I saw was a fitting Plot with no vainly disobey:and the legendary multivariate (linear) regression formula: $Y _{i}=\beta_{0} + \beta_{i1}x_{i1} + \beta_{2}x_{i2} + ... + \beta_{p}x_{ip} + \ep

Summary of the classification of R language common packages

Common packages:--Data processing: Lubridata, Plyr, RESHAPE2,STRINGR,FORMATR,MCMC;--Machine learning: nnet,rpart,tree,party,lars,boost,e1071,bayestree,gafit,arules;--Visual package: Ggplot2,lattice,googlevis;--Map package: Ggmap,rgooglemaps,rworldmap;Financial package:--time series: zoo,xts,chorn,its,timedate;--Financial Analysis: Quantmod,rquantlib,portfolio,performanceanalytics,ttr,sde,yieldcurve;--risk management: PARMA,EVD,EVDBAYES,EVIR,EXTREMES,ISMEV;Data Mining Package:--Cluster Type:--bas

Simple linear regression implemented in PHP: (i)

for PHP. In the early stages, emphasis should be placed on learning to achieve significant analytical testing, as well as addressing the challenges in this area. Instance variables When modeling a statistical test or procedure, you need to indicate which instance variables to declare. The selection of an instance variable can be determined by stating the intermediate value and the total value generated by the analysis process. Each intermediate value and summary value can have a correspondin

Tenth Chapter Variance Analysis _ Variance Analysis

In terms of form, variance analysis is to compare the equality of the average of multiple populations, but in essence it is the relationship between variables. Variance analysis is one of the main methods to study the relationship between one (or more) types of variables and a numerical dependent variable. Introduction to 1 Variance analysis With the increase in the number of individual significant tests, the likelihood of the difference may also increase (not the mean is really different). and

Stata Common Commands Summary (34, including use examples) _stata

-Step Line connection Symbol (abbreviated s)--graphics for individual scatter points: O Big Circle S generous block T Big triangle Type O Small Circle D Small Diamond P Small Plus . Little Bit Gra y x, Xlab Ylab C (L) s (d) Box diagram: Gra y x, oneway/twoway box 26, single sample mean T test: ttest x=14.02 (total mean number μ) Ttesti n Mean sdμ Paired T-Test: TTest x1==x2 T-test of two-sample mean number: TTest x1==x2,unpaired TTest x, by (group) 27, Variance Analysis: Fanchazzi Test: Sdtest

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